Benchmark (ONNX) for DecisionTreeClassifier#
Overview#
(Source code, png, hires.png, pdf)
Detailed graphs#
(Source code, png, hires.png, pdf)
Configuration#
<<<
from pyquickhelper.pandashelper import df2rst
import pandas
name = os.path.join(
__WD__, "../../onnx/results/bench_plot_onnxruntime_decision_tree.time.csv")
df = pandas.read_csv(name)
print(df2rst(df, number_format=4))
>>>
name |
version |
value |
---|---|---|
date |
2019-12-21 |
|
python |
3.7.2 (default, Mar 1 2019, 18:34:21) [GCC 6.3.0 20170516] |
|
platform |
linux |
|
OS |
Linux-4.9.0-8-amd64-x86_64-with-debian-9.6 |
|
machine |
x86_64 |
|
processor |
||
release |
4.9.0-8-amd64 |
|
architecture |
(‘64bit’, ‘’) |
|
mlprodict |
0.3 |
|
numpy |
1.17.4 |
openblas, language=c |
onnx |
1.6.34 |
opset=12 |
onnxruntime |
1.1.995 |
CPU-DNNL-MKL-ML |
pandas |
0.25.3 |
|
skl2onnx |
1.6.994 |
|
sklearn |
0.22 |
Raw results#
bench_plot_onnxruntime_decision_tree.csv
<<<
from pyquickhelper.pandashelper import df2rst
from pymlbenchmark.benchmark.bench_helper import bench_pivot
import pandas
name = os.path.join(
__WD__, "../../onnx/results/bench_plot_onnxruntime_decision_tree.perf.csv")
df = pandas.read_csv(name)
piv = bench_pivot(df).reset_index(drop=False)
piv['speedup_py'] = piv['skl'] / piv['onxpython_compiled']
piv['speedup_ort'] = piv['skl'] / piv['onxonnxruntime1']
print(df2rst(piv, number_format=4))
method |
skl_nb_base_estimators |
N |
dim |
max_depth |
number |
count |
error_c |
onnx_opset |
onxonnxruntime1 |
onxpython_compiled |
skl |
speedup_py |
speedup_ort |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
predict |
-1 |
1 |
1 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
1 |
3 |
1 |
10 |
0 |
12 |
3.655e-05 |
3.292e-05 |
|||
predict |
-1 |
1 |
1 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
1 |
10 |
1 |
10 |
0 |
12 |
3.678e-05 |
2.426e-05 |
|||
predict |
-1 |
1 |
1 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
1 |
20 |
1 |
10 |
0 |
12 |
3.701e-05 |
2.501e-05 |
|||
predict |
-1 |
1 |
5 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
5 |
3 |
1 |
10 |
0 |
12 |
3.701e-05 |
2.42e-05 |
|||
predict |
-1 |
1 |
5 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
5 |
10 |
1 |
10 |
0 |
12 |
3.708e-05 |
2.453e-05 |
|||
predict |
-1 |
1 |
5 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
5 |
20 |
1 |
10 |
0 |
12 |
3.79e-05 |
2.588e-05 |
|||
predict |
-1 |
1 |
10 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
10 |
3 |
1 |
10 |
0 |
12 |
3.774e-05 |
2.458e-05 |
|||
predict |
-1 |
1 |
10 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
10 |
10 |
1 |
10 |
0 |
12 |
3.723e-05 |
2.612e-05 |
|||
predict |
-1 |
1 |
10 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
10 |
20 |
1 |
10 |
0 |
12 |
3.769e-05 |
2.551e-05 |
|||
predict |
-1 |
1 |
20 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
20 |
3 |
1 |
10 |
0 |
12 |
3.953e-05 |
2.514e-05 |
|||
predict |
-1 |
1 |
20 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
20 |
10 |
1 |
10 |
0 |
12 |
3.795e-05 |
2.517e-05 |
|||
predict |
-1 |
1 |
20 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
20 |
20 |
1 |
10 |
0 |
12 |
3.819e-05 |
2.541e-05 |
|||
predict |
-1 |
1 |
50 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
50 |
3 |
1 |
10 |
0 |
12 |
3.764e-05 |
2.636e-05 |
|||
predict |
-1 |
1 |
50 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
50 |
10 |
1 |
10 |
0 |
12 |
3.862e-05 |
2.508e-05 |
|||
predict |
-1 |
1 |
50 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
50 |
20 |
1 |
10 |
0 |
12 |
3.81e-05 |
2.595e-05 |
|||
predict |
-1 |
1 |
100 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
100 |
3 |
1 |
10 |
0 |
12 |
3.932e-05 |
2.486e-05 |
|||
predict |
-1 |
1 |
100 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
100 |
10 |
1 |
10 |
0 |
12 |
3.815e-05 |
2.514e-05 |
|||
predict |
-1 |
1 |
100 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
100 |
20 |
1 |
10 |
0 |
12 |
3.792e-05 |
2.527e-05 |
|||
predict |
-1 |
1 |
200 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
200 |
3 |
1 |
10 |
0 |
12 |
3.817e-05 |
2.53e-05 |
|||
predict |
-1 |
1 |
200 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
200 |
10 |
1 |
10 |
0 |
12 |
3.699e-05 |
2.499e-05 |
|||
predict |
-1 |
1 |
200 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1 |
200 |
20 |
1 |
10 |
0 |
12 |
3.97e-05 |
2.635e-05 |
|||
predict |
-1 |
10 |
1 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
1 |
3 |
1 |
10 |
0 |
12 |
3.421e-05 |
2.553e-05 |
|||
predict |
-1 |
10 |
1 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
1 |
10 |
1 |
10 |
0 |
12 |
3.573e-05 |
2.25e-05 |
|||
predict |
-1 |
10 |
1 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
1 |
20 |
1 |
10 |
0 |
12 |
3.682e-05 |
2.321e-05 |
|||
predict |
-1 |
10 |
5 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
5 |
3 |
1 |
10 |
0 |
12 |
3.466e-05 |
2.211e-05 |
|||
predict |
-1 |
10 |
5 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
5 |
10 |
1 |
10 |
0 |
12 |
3.639e-05 |
2.313e-05 |
|||
predict |
-1 |
10 |
5 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
5 |
20 |
1 |
10 |
0 |
12 |
3.827e-05 |
2.446e-05 |
|||
predict |
-1 |
10 |
10 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
10 |
3 |
1 |
10 |
0 |
12 |
3.505e-05 |
2.229e-05 |
|||
predict |
-1 |
10 |
10 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
10 |
10 |
1 |
10 |
0 |
12 |
3.626e-05 |
2.343e-05 |
|||
predict |
-1 |
10 |
10 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
10 |
20 |
1 |
10 |
0 |
12 |
3.867e-05 |
2.357e-05 |
|||
predict |
-1 |
10 |
20 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
20 |
3 |
1 |
10 |
0 |
12 |
3.553e-05 |
2.301e-05 |
|||
predict |
-1 |
10 |
20 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
20 |
10 |
1 |
10 |
0 |
12 |
3.667e-05 |
2.325e-05 |
|||
predict |
-1 |
10 |
20 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
20 |
20 |
1 |
10 |
0 |
12 |
3.94e-05 |
2.477e-05 |
|||
predict |
-1 |
10 |
50 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
50 |
3 |
1 |
10 |
0 |
12 |
3.687e-05 |
2.304e-05 |
|||
predict |
-1 |
10 |
50 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
50 |
10 |
1 |
10 |
0 |
12 |
3.828e-05 |
2.393e-05 |
|||
predict |
-1 |
10 |
50 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
50 |
20 |
1 |
10 |
0 |
12 |
4.24e-05 |
2.553e-05 |
|||
predict |
-1 |
10 |
100 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
100 |
3 |
1 |
10 |
0 |
12 |
3.727e-05 |
2.346e-05 |
|||
predict |
-1 |
10 |
100 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
100 |
10 |
1 |
10 |
0 |
12 |
3.864e-05 |
2.433e-05 |
|||
predict |
-1 |
10 |
100 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
100 |
20 |
1 |
10 |
0 |
12 |
4.081e-05 |
2.609e-05 |
|||
predict |
-1 |
10 |
200 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
200 |
3 |
1 |
10 |
0 |
12 |
3.801e-05 |
2.458e-05 |
|||
predict |
-1 |
10 |
200 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
200 |
10 |
1 |
10 |
0 |
12 |
3.924e-05 |
2.516e-05 |
|||
predict |
-1 |
10 |
200 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
10 |
200 |
20 |
1 |
10 |
0 |
12 |
4.541e-05 |
2.792e-05 |
|||
predict |
-1 |
100 |
1 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
1 |
3 |
1 |
10 |
0 |
12 |
7.393e-05 |
2.462e-05 |
|||
predict |
-1 |
100 |
1 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
1 |
10 |
1 |
10 |
0 |
12 |
7.843e-05 |
2.494e-05 |
|||
predict |
-1 |
100 |
1 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
1 |
20 |
1 |
10 |
0 |
12 |
8.508e-05 |
2.819e-05 |
|||
predict |
-1 |
100 |
5 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
5 |
3 |
1 |
10 |
0 |
12 |
7.772e-05 |
2.533e-05 |
|||
predict |
-1 |
100 |
5 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
5 |
10 |
1 |
10 |
0 |
12 |
8.099e-05 |
2.764e-05 |
|||
predict |
-1 |
100 |
5 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
5 |
20 |
1 |
10 |
0 |
12 |
9.322e-05 |
3.307e-05 |
|||
predict |
-1 |
100 |
10 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
10 |
3 |
1 |
10 |
0 |
12 |
7.703e-05 |
2.578e-05 |
|||
predict |
-1 |
100 |
10 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
10 |
10 |
1 |
10 |
0 |
12 |
8.14e-05 |
2.811e-05 |
|||
predict |
-1 |
100 |
10 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
10 |
20 |
1 |
10 |
0 |
12 |
9.084e-05 |
3.038e-05 |
|||
predict |
-1 |
100 |
20 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
20 |
3 |
1 |
10 |
0 |
12 |
7.59e-05 |
2.674e-05 |
|||
predict |
-1 |
100 |
20 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
20 |
10 |
1 |
10 |
0 |
12 |
8.279e-05 |
2.888e-05 |
|||
predict |
-1 |
100 |
20 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
20 |
20 |
1 |
10 |
0 |
12 |
9.635e-05 |
3.525e-05 |
|||
predict |
-1 |
100 |
50 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
50 |
3 |
1 |
10 |
0 |
12 |
7.738e-05 |
2.876e-05 |
|||
predict |
-1 |
100 |
50 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
50 |
10 |
1 |
10 |
0 |
12 |
8.254e-05 |
3.059e-05 |
|||
predict |
-1 |
100 |
50 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
50 |
20 |
1 |
10 |
0 |
12 |
0.0001077 |
4.006e-05 |
|||
predict |
-1 |
100 |
100 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
100 |
3 |
1 |
10 |
0 |
12 |
8.086e-05 |
3.254e-05 |
|||
predict |
-1 |
100 |
100 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
100 |
10 |
1 |
10 |
0 |
12 |
8.63e-05 |
3.415e-05 |
|||
predict |
-1 |
100 |
100 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
100 |
20 |
1 |
10 |
0 |
12 |
9.969e-05 |
3.994e-05 |
|||
predict |
-1 |
100 |
200 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
200 |
3 |
1 |
10 |
0 |
12 |
8.644e-05 |
3.861e-05 |
|||
predict |
-1 |
100 |
200 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
200 |
10 |
1 |
10 |
0 |
12 |
9.266e-05 |
4.023e-05 |
|||
predict |
-1 |
100 |
200 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
100 |
200 |
20 |
1 |
10 |
0 |
12 |
0.0001227 |
5.156e-05 |
|||
predict |
-1 |
1000 |
1 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1000 |
1 |
3 |
1 |
10 |
0 |
12 |
0.0004203 |
4.816e-05 |
|||
predict |
-1 |
1000 |
1 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1000 |
1 |
10 |
1 |
10 |
0 |
12 |
0.0004488 |
4.975e-05 |
|||
predict |
-1 |
1000 |
1 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1000 |
1 |
20 |
1 |
10 |
0 |
12 |
0.0004994 |
6.38e-05 |
|||
predict |
-1 |
1000 |
5 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1000 |
5 |
3 |
1 |
10 |
0 |
12 |
0.0004178 |
4.747e-05 |
|||
predict |
-1 |
1000 |
5 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1000 |
5 |
10 |
1 |
10 |
0 |
12 |
0.004576 |
6.036e-05 |
|||
predict |
-1 |
1000 |
5 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1000 |
5 |
20 |
1 |
10 |
0 |
12 |
0.0005285 |
8.213e-05 |
|||
predict |
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1000 |
10 |
3 |
1 |
10 |
0 |
-1 |
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predict |
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1000 |
10 |
3 |
1 |
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0 |
12 |
0.0004516 |
5.117e-05 |
|||
predict |
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1000 |
10 |
10 |
1 |
10 |
0 |
-1 |
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predict |
-1 |
1000 |
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10 |
1 |
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0 |
12 |
0.0004649 |
6.624e-05 |
|||
predict |
-1 |
1000 |
10 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1000 |
10 |
20 |
1 |
10 |
0 |
12 |
0.0005278 |
7.932e-05 |
|||
predict |
-1 |
1000 |
20 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict |
-1 |
1000 |
20 |
3 |
1 |
10 |
0 |
12 |
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predict |
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1 |
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||||
predict |
1 |
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1 |
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||||
predict |
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1 |
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||||
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1 |
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||||
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1 |
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||||
predict |
1 |
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predict |
1 |
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predict_proba |
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2.882e-05 |
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predict_proba |
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predict_proba |
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2.988e-05 |
2.095e-05 |
|||
predict_proba |
-1 |
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predict_proba |
-1 |
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0 |
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2.984e-05 |
2.163e-05 |
|||
predict_proba |
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|||||
predict_proba |
-1 |
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0 |
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2.916e-05 |
2.09e-05 |
|||
predict_proba |
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10 |
1 |
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-1 |
|||||
predict_proba |
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5 |
10 |
1 |
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0 |
12 |
3.026e-05 |
2.129e-05 |
|||
predict_proba |
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1 |
5 |
20 |
1 |
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-1 |
|||||
predict_proba |
-1 |
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5 |
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1 |
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0 |
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2.971e-05 |
2.145e-05 |
|||
predict_proba |
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1 |
10 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
10 |
3 |
1 |
10 |
0 |
12 |
3.07e-05 |
2.172e-05 |
|||
predict_proba |
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1 |
10 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
10 |
10 |
1 |
10 |
0 |
12 |
2.951e-05 |
2.137e-05 |
|||
predict_proba |
-1 |
1 |
10 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
10 |
20 |
1 |
10 |
0 |
12 |
2.976e-05 |
2.174e-05 |
|||
predict_proba |
-1 |
1 |
20 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
20 |
3 |
1 |
10 |
0 |
12 |
3.08e-05 |
2.212e-05 |
|||
predict_proba |
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1 |
20 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
20 |
10 |
1 |
10 |
0 |
12 |
3.212e-05 |
2.165e-05 |
|||
predict_proba |
-1 |
1 |
20 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
20 |
20 |
1 |
10 |
0 |
12 |
2.962e-05 |
2.171e-05 |
|||
predict_proba |
-1 |
1 |
50 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
50 |
3 |
1 |
10 |
0 |
12 |
3.038e-05 |
2.224e-05 |
|||
predict_proba |
-1 |
1 |
50 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
50 |
10 |
1 |
10 |
0 |
12 |
3.035e-05 |
2.188e-05 |
|||
predict_proba |
-1 |
1 |
50 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
50 |
20 |
1 |
10 |
0 |
12 |
2.976e-05 |
2.201e-05 |
|||
predict_proba |
-1 |
1 |
100 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
100 |
3 |
1 |
10 |
0 |
12 |
3.085e-05 |
2.262e-05 |
|||
predict_proba |
-1 |
1 |
100 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
100 |
10 |
1 |
10 |
0 |
12 |
2.938e-05 |
2.127e-05 |
|||
predict_proba |
-1 |
1 |
100 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
100 |
20 |
1 |
10 |
0 |
12 |
2.949e-05 |
2.168e-05 |
|||
predict_proba |
-1 |
1 |
200 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
200 |
3 |
1 |
10 |
0 |
12 |
3.005e-05 |
2.204e-05 |
|||
predict_proba |
-1 |
1 |
200 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
200 |
10 |
1 |
10 |
0 |
12 |
2.972e-05 |
2.135e-05 |
|||
predict_proba |
-1 |
1 |
200 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
1 |
200 |
20 |
1 |
10 |
0 |
12 |
2.999e-05 |
2.166e-05 |
|||
predict_proba |
-1 |
10 |
1 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
1 |
3 |
1 |
10 |
0 |
12 |
3.38e-05 |
2.107e-05 |
|||
predict_proba |
-1 |
10 |
1 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
1 |
10 |
1 |
10 |
0 |
12 |
3.352e-05 |
2.149e-05 |
|||
predict_proba |
-1 |
10 |
1 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
1 |
20 |
1 |
10 |
0 |
12 |
3.45e-05 |
2.2e-05 |
|||
predict_proba |
-1 |
10 |
5 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
5 |
3 |
1 |
10 |
0 |
12 |
3.366e-05 |
2.115e-05 |
|||
predict_proba |
-1 |
10 |
5 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
5 |
10 |
1 |
10 |
0 |
12 |
3.399e-05 |
2.208e-05 |
|||
predict_proba |
-1 |
10 |
5 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
5 |
20 |
1 |
10 |
0 |
12 |
3.621e-05 |
2.295e-05 |
|||
predict_proba |
-1 |
10 |
10 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
10 |
3 |
1 |
10 |
0 |
12 |
3.369e-05 |
2.107e-05 |
|||
predict_proba |
-1 |
10 |
10 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
10 |
10 |
1 |
10 |
0 |
12 |
3.406e-05 |
2.226e-05 |
|||
predict_proba |
-1 |
10 |
10 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
10 |
20 |
1 |
10 |
0 |
12 |
3.487e-05 |
2.245e-05 |
|||
predict_proba |
-1 |
10 |
20 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
20 |
3 |
1 |
10 |
0 |
12 |
3.346e-05 |
2.134e-05 |
|||
predict_proba |
-1 |
10 |
20 |
10 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
20 |
10 |
1 |
10 |
0 |
12 |
3.443e-05 |
2.212e-05 |
|||
predict_proba |
-1 |
10 |
20 |
20 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
20 |
20 |
1 |
10 |
0 |
12 |
3.599e-05 |
2.359e-05 |
|||
predict_proba |
-1 |
10 |
50 |
3 |
1 |
10 |
0 |
-1 |
|||||
predict_proba |
-1 |
10 |
50 |
3 |
1 |
10 |
0 |
12 |
3.538e-05 |
2.234e-05 |
|||
predict_proba |
-1 |
10 |
50 |
10 |
1 |
10 |
0 |
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-1 |
10 |
50 |
10 |
1 |
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3.603e-05 |
2.265e-05 |
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3.765e-05 |
2.454e-05 |
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predict_proba |
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3.535e-05 |
2.249e-05 |
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3.629e-05 |
2.296e-05 |
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predict_proba |
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3.721e-05 |
2.398e-05 |
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predict_proba |
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3.635e-05 |
2.333e-05 |
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3.846e-05 |
2.404e-05 |
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3.984e-05 |
2.51e-05 |
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predict_proba |
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predict_proba |
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1 |
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8.003e-05 |
2.366e-05 |
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predict_proba |
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predict_proba |
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7.974e-05 |
2.368e-05 |
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8.666e-05 |
2.669e-05 |
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predict_proba |
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predict_proba |
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7.757e-05 |
2.406e-05 |
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predict_proba |
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predict_proba |
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8.248e-05 |
2.715e-05 |
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predict_proba |
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predict_proba |
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9.118e-05 |
2.988e-05 |
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predict_proba |
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predict_proba |
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8.075e-05 |
2.457e-05 |
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predict_proba |
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10 |
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predict_proba |
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10 |
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1 |
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8.485e-05 |
2.7e-05 |
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predict_proba |
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1 |
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predict_proba |
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10 |
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9.211e-05 |
2.854e-05 |
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predict_proba |
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1 |
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predict_proba |
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20 |
3 |
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8.108e-05 |
2.619e-05 |
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predict_proba |
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10 |
1 |
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predict_proba |
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100 |
20 |
10 |
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8.688e-05 |
2.763e-05 |
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predict_proba |
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1 |
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predict_proba |
-1 |
100 |
20 |
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9.435e-05 |
3.279e-05 |
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predict_proba |
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50 |
3 |
1 |
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predict_proba |
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100 |
50 |
3 |
1 |
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8.237e-05 |
2.768e-05 |
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predict_proba |
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1 |
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predict_proba |
-1 |
100 |
50 |
10 |
1 |
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8.609e-05 |
2.927e-05 |
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predict_proba |
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50 |
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1 |
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predict_proba |
-1 |
100 |
50 |
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1 |
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0 |
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0.0001015 |
3.59e-05 |
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predict_proba |
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100 |
100 |
3 |
1 |
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0 |
-1 |
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predict_proba |
-1 |
100 |
100 |
3 |
1 |
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0 |
12 |
8.537e-05 |
3.178e-05 |
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predict_proba |
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100 |
100 |
10 |
1 |
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-1 |
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predict_proba |
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100 |
100 |
10 |
1 |
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0 |
12 |
9.262e-05 |
3.338e-05 |
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predict_proba |
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100 |
100 |
20 |
1 |
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0 |
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predict_proba |
-1 |
100 |
100 |
20 |
1 |
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9.942e-05 |
3.838e-05 |
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predict_proba |
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100 |
200 |
3 |
1 |
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0 |
-1 |
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predict_proba |
-1 |
100 |
200 |
3 |
1 |
10 |
0 |
12 |
9.367e-05 |
3.716e-05 |
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predict_proba |
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100 |
200 |
10 |
1 |
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0 |
-1 |
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predict_proba |
-1 |
100 |
200 |
10 |
1 |
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0 |
12 |
9.919e-05 |
3.95e-05 |
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predict_proba |
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100 |
200 |
20 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
100 |
200 |
20 |
1 |
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0 |
12 |
0.0001158 |
4.631e-05 |
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predict_proba |
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1000 |
1 |
3 |
1 |
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0 |
-1 |
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predict_proba |
-1 |
1000 |
1 |
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1 |
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0.0004481 |
4.569e-05 |
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predict_proba |
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1 |
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1 |
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-1 |
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predict_proba |
-1 |
1000 |
1 |
10 |
1 |
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0 |
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0.0004221 |
4.738e-05 |
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predict_proba |
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1 |
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1 |
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-1 |
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predict_proba |
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1000 |
1 |
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1 |
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0 |
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0.0004728 |
6.411e-05 |
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predict_proba |
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5 |
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1 |
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predict_proba |
-1 |
1000 |
5 |
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1 |
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0.0003841 |
4.551e-05 |
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predict_proba |
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-1 |
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predict_proba |
-1 |
1000 |
5 |
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1 |
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0.000464 |
6.04e-05 |
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predict_proba |
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5 |
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predict_proba |
-1 |
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5 |
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0.0004865 |
7.805e-05 |
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predict_proba |
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-1 |
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predict_proba |
-1 |
1000 |
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1 |
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0 |
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0.0004163 |
4.852e-05 |
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predict_proba |
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1 |
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predict_proba |
-1 |
1000 |
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1 |
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0 |
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0.0004284 |
6.233e-05 |
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predict_proba |
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predict_proba |
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1000 |
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1 |
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0.0004859 |
7.506e-05 |
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predict_proba |
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predict_proba |
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0.0003932 |
6.155e-05 |
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predict_proba |
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predict_proba |
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0.0004492 |
6.705e-05 |
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predict_proba |
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0.0005197 |
9.811e-05 |
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predict_proba |
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predict_proba |
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0.0004219 |
7.195e-05 |
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predict_proba |
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0.0004644 |
8.376e-05 |
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predict_proba |
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predict_proba |
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1 |
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0.0005904 |
0.0001313 |
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predict_proba |
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predict_proba |
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1000 |
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0.0004661 |
0.000109 |
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predict_proba |
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predict_proba |
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1000 |
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1 |
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0.0005111 |
0.0001198 |
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predict_proba |
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100 |
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1 |
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0 |
-1 |
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predict_proba |
-1 |
1000 |
100 |
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1 |
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0 |
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0.0006013 |
0.0001518 |
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predict_proba |
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1000 |
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1 |
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0 |
-1 |
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predict_proba |
-1 |
1000 |
200 |
3 |
1 |
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0 |
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0.0005447 |
0.0001804 |
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predict_proba |
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1 |
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0 |
-1 |
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predict_proba |
-1 |
1000 |
200 |
10 |
1 |
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0 |
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0.0005843 |
0.000194 |
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predict_proba |
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1000 |
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1 |
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0 |
-1 |
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predict_proba |
-1 |
1000 |
200 |
20 |
1 |
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0 |
12 |
0.0007538 |
0.0002558 |
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predict_proba |
-1 |
10000 |
1 |
3 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
1 |
3 |
1 |
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0 |
12 |
0.004046 |
0.0002603 |
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predict_proba |
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10000 |
1 |
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1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
1 |
10 |
1 |
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0 |
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0.004322 |
0.0002668 |
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predict_proba |
-1 |
10000 |
1 |
20 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
1 |
20 |
1 |
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0 |
12 |
0.004769 |
0.0003949 |
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predict_proba |
-1 |
10000 |
5 |
3 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
5 |
3 |
1 |
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0 |
12 |
0.003871 |
0.0002737 |
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predict_proba |
-1 |
10000 |
5 |
10 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
5 |
10 |
1 |
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0 |
12 |
0.004267 |
0.0003478 |
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predict_proba |
-1 |
10000 |
5 |
20 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
5 |
20 |
1 |
10 |
0 |
12 |
0.004753 |
0.0005292 |
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predict_proba |
-1 |
10000 |
10 |
3 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
10 |
3 |
1 |
10 |
0 |
12 |
0.003768 |
0.0002993 |
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predict_proba |
-1 |
10000 |
10 |
10 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
10 |
10 |
1 |
10 |
0 |
12 |
0.0041 |
0.0003995 |
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predict_proba |
-1 |
10000 |
10 |
20 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
10 |
20 |
1 |
10 |
0 |
12 |
0.004617 |
0.0005079 |
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predict_proba |
-1 |
10000 |
20 |
3 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
20 |
3 |
1 |
10 |
0 |
12 |
0.003733 |
0.0003632 |
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predict_proba |
-1 |
10000 |
20 |
10 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
20 |
10 |
1 |
10 |
0 |
12 |
0.00415 |
0.0004421 |
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predict_proba |
-1 |
10000 |
20 |
20 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
20 |
20 |
1 |
10 |
0 |
12 |
0.004855 |
0.0006979 |
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predict_proba |
-1 |
10000 |
50 |
3 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
50 |
3 |
1 |
10 |
0 |
12 |
0.003848 |
0.0005521 |
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predict_proba |
-1 |
10000 |
50 |
10 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
50 |
10 |
1 |
10 |
0 |
12 |
0.004271 |
0.0006416 |
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predict_proba |
-1 |
10000 |
50 |
20 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
50 |
20 |
1 |
10 |
0 |
12 |
0.005572 |
0.001021 |
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predict_proba |
-1 |
10000 |
100 |
3 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
100 |
3 |
1 |
10 |
0 |
12 |
0.004481 |
0.0009976 |
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predict_proba |
-1 |
10000 |
100 |
10 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
100 |
10 |
1 |
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0 |
12 |
0.004793 |
0.001055 |
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predict_proba |
-1 |
10000 |
100 |
20 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
100 |
20 |
1 |
10 |
0 |
12 |
0.005661 |
0.001287 |
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predict_proba |
-1 |
10000 |
200 |
3 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
200 |
3 |
1 |
10 |
0 |
12 |
0.005671 |
0.002053 |
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predict_proba |
-1 |
10000 |
200 |
10 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
200 |
10 |
1 |
10 |
0 |
12 |
0.006087 |
0.00205 |
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predict_proba |
-1 |
10000 |
200 |
20 |
1 |
10 |
0 |
-1 |
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predict_proba |
-1 |
10000 |
200 |
20 |
1 |
10 |
0 |
12 |
0.00856 |
0.002774 |
|||
predict_proba |
1 |
1 |
1 |
3 |
1 |
10 |
0 |
-1 |
7.812e-05 |
||||
predict_proba |
1 |
1 |
1 |
3 |
1 |
10 |
0 |
12 |
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predict_proba |
1 |
1 |
1 |
10 |
1 |
10 |
0 |
-1 |
7.728e-05 |
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predict_proba |
1 |
1 |
1 |
10 |
1 |
10 |
0 |
12 |
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predict_proba |
1 |
1 |
1 |
20 |
1 |
10 |
0 |
-1 |
7.815e-05 |
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predict_proba |
1 |
1 |
1 |
20 |
1 |
10 |
0 |
12 |
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predict_proba |
1 |
1 |
5 |
3 |
1 |
10 |
0 |
-1 |
7.777e-05 |
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predict_proba |
1 |
1 |
5 |
3 |
1 |
10 |
0 |
12 |
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predict_proba |
1 |
1 |
5 |
10 |
1 |
10 |
0 |
-1 |
7.616e-05 |
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predict_proba |
1 |
1 |
5 |
10 |
1 |
10 |
0 |
12 |
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predict_proba |
1 |
1 |
5 |
20 |
1 |
10 |
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7.698e-05 |
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predict_proba |
1 |
1 |
5 |
20 |
1 |
10 |
0 |
12 |
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predict_proba |
1 |
1 |
10 |
3 |
1 |
10 |
0 |
-1 |
7.67e-05 |
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predict_proba |
1 |
1 |
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12 |
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1 |
1 |
10 |
10 |
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7.746e-05 |
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7.701e-05 |
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7.872e-05 |
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7.842e-05 |
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7.877e-05 |
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7.764e-05 |
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7.842e-05 |
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7.834e-05 |
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predict_proba |
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7.669e-05 |
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7.743e-05 |
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7.783e-05 |
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7.861e-05 |
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7.603e-05 |
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7.993e-05 |
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8.023e-05 |
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7.837e-05 |
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8.121e-05 |
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predict_proba |
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7.801e-05 |
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predict_proba |
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7.964e-05 |
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predict_proba |
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8.079e-05 |
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predict_proba |
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predict_proba |
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7.881e-05 |
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predict_proba |
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predict_proba |
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7.906e-05 |
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predict_proba |
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predict_proba |
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8.042e-05 |
||||
predict_proba |
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predict_proba |
1 |
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7.977e-05 |
||||
predict_proba |
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predict_proba |
1 |
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7.825e-05 |
||||
predict_proba |
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1 |
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12 |
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predict_proba |
1 |
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20 |
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1 |
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-1 |
8.039e-05 |
||||
predict_proba |
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20 |
1 |
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0 |
12 |
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predict_proba |
1 |
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50 |
3 |
1 |
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-1 |
8.113e-05 |
||||
predict_proba |
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1 |
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0 |
12 |
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predict_proba |
1 |
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1 |
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8.181e-05 |
||||
predict_proba |
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10 |
1 |
10 |
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12 |
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predict_proba |
1 |
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1 |
10 |
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-1 |
8.27e-05 |
||||
predict_proba |
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1 |
10 |
0 |
12 |
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predict_proba |
1 |
10 |
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3 |
1 |
10 |
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-1 |
8.105e-05 |
||||
predict_proba |
1 |
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3 |
1 |
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0 |
12 |
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predict_proba |
1 |
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100 |
10 |
1 |
10 |
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-1 |
8.027e-05 |
||||
predict_proba |
1 |
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100 |
10 |
1 |
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0 |
12 |
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predict_proba |
1 |
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100 |
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1 |
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-1 |
8.202e-05 |
||||
predict_proba |
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100 |
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1 |
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0 |
12 |
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predict_proba |
1 |
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3 |
1 |
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-1 |
7.961e-05 |
||||
predict_proba |
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1 |
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12 |
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predict_proba |
1 |
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1 |
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-1 |
8.097e-05 |
||||
predict_proba |
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1 |
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12 |
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predict_proba |
1 |
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-1 |
8.212e-05 |
||||
predict_proba |
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1 |
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12 |
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predict_proba |
1 |
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8.444e-05 |
||||
predict_proba |
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1 |
3 |
1 |
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12 |
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predict_proba |
1 |
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8.951e-05 |
||||
predict_proba |
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12 |
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predict_proba |
1 |
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8.801e-05 |
||||
predict_proba |
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1 |
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12 |
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predict_proba |
1 |
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8.22e-05 |
||||
predict_proba |
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1 |
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12 |
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predict_proba |
1 |
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8.688e-05 |
||||
predict_proba |
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1 |
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12 |
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predict_proba |
1 |
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9.176e-05 |
||||
predict_proba |
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1 |
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12 |
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predict_proba |
1 |
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-1 |
8.24e-05 |
||||
predict_proba |
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1 |
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12 |
|||||
predict_proba |
1 |
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1 |
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8.739e-05 |
||||
predict_proba |
1 |
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10 |
1 |
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0 |
12 |
|||||
predict_proba |
1 |
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1 |
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-1 |
9.149e-05 |
||||
predict_proba |
1 |
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1 |
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12 |
|||||
predict_proba |
1 |
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1 |
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-1 |
8.359e-05 |
||||
predict_proba |
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3 |
1 |
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12 |
|||||
predict_proba |
1 |
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1 |
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-1 |
8.713e-05 |
||||
predict_proba |
1 |
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1 |
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12 |
|||||
predict_proba |
1 |
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1 |
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9.553e-05 |
||||
predict_proba |
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20 |
1 |
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12 |
|||||
predict_proba |
1 |
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1 |
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-1 |
8.504e-05 |
||||
predict_proba |
1 |
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3 |
1 |
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12 |
|||||
predict_proba |
1 |
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1 |
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8.987e-05 |
||||
predict_proba |
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1 |
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12 |
|||||
predict_proba |
1 |
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1 |
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-1 |
9.778e-05 |
||||
predict_proba |
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1 |
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12 |
|||||
predict_proba |
1 |
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1 |
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8.833e-05 |
||||
predict_proba |
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1 |
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12 |
|||||
predict_proba |
1 |
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1 |
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-1 |
9.193e-05 |
||||
predict_proba |
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1 |
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12 |
|||||
predict_proba |
1 |
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9.939e-05 |
||||
predict_proba |
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1 |
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12 |
|||||
predict_proba |
1 |
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1 |
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9.324e-05 |
||||
predict_proba |
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1 |
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12 |
|||||
predict_proba |
1 |
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1 |
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9.793e-05 |
||||
predict_proba |
1 |
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1 |
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12 |
|||||
predict_proba |
1 |
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1 |
10 |
0 |
-1 |
0.0001092 |
||||
predict_proba |
1 |
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200 |
20 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
1000 |
1 |
3 |
1 |
10 |
0 |
-1 |
0.0001184 |
||||
predict_proba |
1 |
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1 |
3 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
1000 |
1 |
10 |
1 |
10 |
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0.0001353 |
||||
predict_proba |
1 |
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1 |
10 |
1 |
10 |
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12 |
|||||
predict_proba |
1 |
1000 |
1 |
20 |
1 |
10 |
0 |
-1 |
0.0001763 |
||||
predict_proba |
1 |
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1 |
20 |
1 |
10 |
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12 |
|||||
predict_proba |
1 |
1000 |
5 |
3 |
1 |
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0.0001133 |
||||
predict_proba |
1 |
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5 |
3 |
1 |
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|||||
predict_proba |
1 |
1000 |
5 |
10 |
1 |
10 |
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0.000163 |
||||
predict_proba |
1 |
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5 |
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1 |
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|||||
predict_proba |
1 |
1000 |
5 |
20 |
1 |
10 |
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0.000195 |
||||
predict_proba |
1 |
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5 |
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1 |
10 |
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12 |
|||||
predict_proba |
1 |
1000 |
10 |
3 |
1 |
10 |
0 |
-1 |
0.0001172 |
||||
predict_proba |
1 |
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1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
1000 |
10 |
10 |
1 |
10 |
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0.0001514 |
||||
predict_proba |
1 |
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1 |
10 |
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12 |
|||||
predict_proba |
1 |
1000 |
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1 |
10 |
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0.0001908 |
||||
predict_proba |
1 |
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1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
1000 |
20 |
3 |
1 |
10 |
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0.0001224 |
||||
predict_proba |
1 |
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1 |
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12 |
|||||
predict_proba |
1 |
1000 |
20 |
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1 |
10 |
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-1 |
0.0001575 |
||||
predict_proba |
1 |
1000 |
20 |
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1 |
10 |
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12 |
|||||
predict_proba |
1 |
1000 |
20 |
20 |
1 |
10 |
0 |
-1 |
0.0002116 |
||||
predict_proba |
1 |
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1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
1000 |
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3 |
1 |
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0.0001407 |
||||
predict_proba |
1 |
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1 |
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predict_proba |
1 |
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1 |
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0.0001761 |
||||
predict_proba |
1 |
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1 |
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|||||
predict_proba |
1 |
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50 |
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1 |
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0.0002612 |
||||
predict_proba |
1 |
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1 |
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|||||
predict_proba |
1 |
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3 |
1 |
10 |
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0.0001813 |
||||
predict_proba |
1 |
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1 |
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12 |
|||||
predict_proba |
1 |
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100 |
10 |
1 |
10 |
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0.0002165 |
||||
predict_proba |
1 |
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1 |
10 |
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12 |
|||||
predict_proba |
1 |
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1 |
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0.0002755 |
||||
predict_proba |
1 |
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1 |
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|||||
predict_proba |
1 |
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3 |
1 |
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0.0002549 |
||||
predict_proba |
1 |
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1 |
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predict_proba |
1 |
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1 |
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0.0002833 |
||||
predict_proba |
1 |
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1 |
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|||||
predict_proba |
1 |
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1 |
10 |
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0.0003897 |
||||
predict_proba |
1 |
1000 |
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1 |
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0 |
12 |
|||||
predict_proba |
1 |
10000 |
1 |
3 |
1 |
10 |
0 |
-1 |
0.0004688 |
||||
predict_proba |
1 |
10000 |
1 |
3 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
1 |
10 |
1 |
10 |
0 |
-1 |
0.0006517 |
||||
predict_proba |
1 |
10000 |
1 |
10 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
1 |
20 |
1 |
10 |
0 |
-1 |
0.001048 |
||||
predict_proba |
1 |
10000 |
1 |
20 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
5 |
3 |
1 |
10 |
0 |
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0.0004596 |
||||
predict_proba |
1 |
10000 |
5 |
3 |
1 |
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0 |
12 |
|||||
predict_proba |
1 |
10000 |
5 |
10 |
1 |
10 |
0 |
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0.0007673 |
||||
predict_proba |
1 |
10000 |
5 |
10 |
1 |
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0 |
12 |
|||||
predict_proba |
1 |
10000 |
5 |
20 |
1 |
10 |
0 |
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0.001187 |
||||
predict_proba |
1 |
10000 |
5 |
20 |
1 |
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0 |
12 |
|||||
predict_proba |
1 |
10000 |
10 |
3 |
1 |
10 |
0 |
-1 |
0.0004922 |
||||
predict_proba |
1 |
10000 |
10 |
3 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
10 |
10 |
1 |
10 |
0 |
-1 |
0.0008159 |
||||
predict_proba |
1 |
10000 |
10 |
10 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
10 |
20 |
1 |
10 |
0 |
-1 |
0.00118 |
||||
predict_proba |
1 |
10000 |
10 |
20 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
20 |
3 |
1 |
10 |
0 |
-1 |
0.0005704 |
||||
predict_proba |
1 |
10000 |
20 |
3 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
20 |
10 |
1 |
10 |
0 |
-1 |
0.0008705 |
||||
predict_proba |
1 |
10000 |
20 |
10 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
20 |
20 |
1 |
10 |
0 |
-1 |
0.001378 |
||||
predict_proba |
1 |
10000 |
20 |
20 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
50 |
3 |
1 |
10 |
0 |
-1 |
0.0007826 |
||||
predict_proba |
1 |
10000 |
50 |
3 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
50 |
10 |
1 |
10 |
0 |
-1 |
0.001097 |
||||
predict_proba |
1 |
10000 |
50 |
10 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
50 |
20 |
1 |
10 |
0 |
-1 |
0.001833 |
||||
predict_proba |
1 |
10000 |
50 |
20 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
100 |
3 |
1 |
10 |
0 |
-1 |
0.001275 |
||||
predict_proba |
1 |
10000 |
100 |
3 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
100 |
10 |
1 |
10 |
0 |
-1 |
0.00155 |
||||
predict_proba |
1 |
10000 |
100 |
10 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
100 |
20 |
1 |
10 |
0 |
-1 |
0.002096 |
||||
predict_proba |
1 |
10000 |
100 |
20 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
200 |
3 |
1 |
10 |
0 |
-1 |
0.002302 |
||||
predict_proba |
1 |
10000 |
200 |
3 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
200 |
10 |
1 |
10 |
0 |
-1 |
0.002664 |
||||
predict_proba |
1 |
10000 |
200 |
10 |
1 |
10 |
0 |
12 |
|||||
predict_proba |
1 |
10000 |
200 |
20 |
1 |
10 |
0 |
-1 |
0.003636 |
||||
predict_proba |
1 |
10000 |
200 |
20 |
1 |
10 |
0 |
12 |
<<<
from pyquickhelper.pandashelper import df2rst
import pandas
name = os.path.join(
__WD__, "../../onnx/results/bench_plot_onnxruntime_decision_tree.perf.csv")
df = pandas.read_csv(name)
df = df[df['lib'] == 'skl']
print(df2rst(df, number_format=4))
method |
lib |
skl_nb_base_estimators |
skl_dt_nodes |
N |
dim |
max_depth |
repeat |
number |
min |
max |
min3 |
max3 |
mean |
lower |
upper |
count |
median |
error_c |
onnx_nodes |
onnx_opset |
ort_size |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
predict |
skl |
1 |
15 |
1 |
1 |
3 |
10 |
1 |
5.418e-05 |
0.0002216 |
5.621e-05 |
6.2e-05 |
7.489e-05 |
5.418e-05 |
0.000171 |
10 |
5.804e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
1 |
1 |
3 |
10 |
1 |
6.812e-05 |
9.504e-05 |
7.479e-05 |
7.938e-05 |
7.812e-05 |
6.812e-05 |
9.195e-05 |
10 |
7.685e-05 |
0 |
|||
predict |
skl |
1 |
15 |
10 |
1 |
3 |
10 |
1 |
5.395e-05 |
7.305e-05 |
5.494e-05 |
5.993e-05 |
5.843e-05 |
5.395e-05 |
6.953e-05 |
10 |
5.631e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
10 |
1 |
3 |
10 |
1 |
7.007e-05 |
8.983e-05 |
7.872e-05 |
8.365e-05 |
8.023e-05 |
7.038e-05 |
8.983e-05 |
10 |
7.997e-05 |
0 |
|||
predict |
skl |
1 |
15 |
100 |
1 |
3 |
10 |
1 |
5.896e-05 |
8.436e-05 |
5.991e-05 |
6.307e-05 |
6.394e-05 |
5.896e-05 |
7.823e-05 |
10 |
6.161e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
100 |
1 |
3 |
10 |
1 |
7.459e-05 |
9.597e-05 |
7.86e-05 |
8.993e-05 |
8.444e-05 |
7.459e-05 |
9.597e-05 |
10 |
8.327e-05 |
0 |
|||
predict |
skl |
1 |
15 |
1000 |
1 |
3 |
10 |
1 |
8.485e-05 |
0.0001061 |
8.596e-05 |
8.955e-05 |
8.949e-05 |
8.485e-05 |
0.0001013 |
10 |
8.755e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
1000 |
1 |
3 |
10 |
1 |
0.0001149 |
0.000129 |
0.0001162 |
0.0001185 |
0.0001184 |
0.0001149 |
0.0001264 |
10 |
0.0001164 |
0 |
|||
predict |
skl |
1 |
15 |
10000 |
1 |
3 |
10 |
1 |
0.0003005 |
0.0003809 |
0.0003019 |
0.000316 |
0.000314 |
0.0003005 |
0.0003596 |
10 |
0.0003033 |
0 |
|||
predict_proba |
skl |
1 |
15 |
10000 |
1 |
3 |
10 |
1 |
0.0004521 |
0.0005165 |
0.0004565 |
0.0004726 |
0.0004688 |
0.0004521 |
0.0005094 |
10 |
0.0004578 |
0 |
|||
predict |
skl |
1 |
191 |
1 |
1 |
10 |
10 |
1 |
5.272e-05 |
0.0008473 |
5.425e-05 |
6.593e-05 |
0.0001363 |
5.272e-05 |
0.0006009 |
10 |
5.468e-05 |
0 |
|||
predict_proba |
skl |
1 |
191 |
1 |
1 |
10 |
10 |
1 |
6.811e-05 |
9.107e-05 |
7.49e-05 |
8.081e-05 |
7.728e-05 |
6.811e-05 |
8.867e-05 |
10 |
7.571e-05 |
0 |
|||
predict |
skl |
1 |
191 |
10 |
1 |
10 |
10 |
1 |
5.405e-05 |
7.062e-05 |
5.498e-05 |
5.808e-05 |
5.779e-05 |
5.405e-05 |
6.734e-05 |
10 |
5.589e-05 |
0 |
|||
predict_proba |
skl |
1 |
191 |
10 |
1 |
10 |
10 |
1 |
7.032e-05 |
8.862e-05 |
7.606e-05 |
8.001e-05 |
7.837e-05 |
7.032e-05 |
8.764e-05 |
10 |
7.812e-05 |
0 |
|||
predict |
skl |
1 |
191 |
100 |
1 |
10 |
10 |
1 |
5.843e-05 |
8.09e-05 |
6.14e-05 |
6.511e-05 |
6.41e-05 |
5.843e-05 |
7.638e-05 |
10 |
6.225e-05 |
0 |
|||
predict_proba |
skl |
1 |
191 |
100 |
1 |
10 |
10 |
1 |
7.704e-05 |
0.0001258 |
7.915e-05 |
9.701e-05 |
8.951e-05 |
7.704e-05 |
0.0001172 |
10 |
8.58e-05 |
0 |
|||
predict |
skl |
1 |
191 |
1000 |
1 |
10 |
10 |
1 |
9.96e-05 |
0.0001234 |
0.0001005 |
0.0001046 |
0.0001043 |
9.96e-05 |
0.0001179 |
10 |
0.0001013 |
0 |
|||
predict_proba |
skl |
1 |
191 |
1000 |
1 |
10 |
10 |
1 |
0.0001294 |
0.0001471 |
0.0001319 |
0.0001371 |
0.0001353 |
0.0001294 |
0.0001471 |
10 |
0.0001325 |
0 |
|||
predict |
skl |
1 |
191 |
10000 |
1 |
10 |
10 |
1 |
0.0004757 |
0.0005637 |
0.0004775 |
0.0005269 |
0.0004976 |
0.0004757 |
0.0005563 |
10 |
0.0004796 |
0 |
|||
predict_proba |
skl |
1 |
191 |
10000 |
1 |
10 |
10 |
1 |
0.0006372 |
0.0007088 |
0.0006394 |
0.0006483 |
0.0006517 |
0.0006372 |
0.0006956 |
10 |
0.0006415 |
0 |
|||
predict |
skl |
1 |
1789 |
1 |
1 |
20 |
10 |
1 |
5.26e-05 |
0.0008466 |
5.392e-05 |
5.859e-05 |
0.0001353 |
5.26e-05 |
0.0006001 |
10 |
5.458e-05 |
0 |
|||
predict_proba |
skl |
1 |
1789 |
1 |
1 |
20 |
10 |
1 |
7.039e-05 |
9.168e-05 |
7.566e-05 |
8.09e-05 |
7.815e-05 |
7.039e-05 |
8.886e-05 |
10 |
7.629e-05 |
0 |
|||
predict |
skl |
1 |
1789 |
10 |
1 |
20 |
10 |
1 |
5.581e-05 |
7.194e-05 |
5.674e-05 |
6.05e-05 |
5.937e-05 |
5.581e-05 |
6.86e-05 |
10 |
5.743e-05 |
0 |
|||
predict_proba |
skl |
1 |
1789 |
10 |
1 |
20 |
10 |
1 |
7.58e-05 |
9.15e-05 |
7.907e-05 |
8.373e-05 |
8.121e-05 |
7.58e-05 |
8.989e-05 |
10 |
8.028e-05 |
0 |
|||
predict |
skl |
1 |
1789 |
100 |
1 |
20 |
10 |
1 |
6.577e-05 |
9.582e-05 |
6.967e-05 |
7.613e-05 |
7.494e-05 |
6.577e-05 |
9.244e-05 |
10 |
7.141e-05 |
0 |
|||
predict_proba |
skl |
1 |
1789 |
100 |
1 |
20 |
10 |
1 |
8.021e-05 |
0.0001031 |
8.367e-05 |
9.679e-05 |
8.801e-05 |
8.021e-05 |
0.000103 |
10 |
8.461e-05 |
0 |
|||
predict |
skl |
1 |
1789 |
1000 |
1 |
20 |
10 |
1 |
0.0001397 |
0.0001735 |
0.0001413 |
0.0001467 |
0.0001463 |
0.0001397 |
0.0001653 |
10 |
0.000143 |
0 |
|||
predict_proba |
skl |
1 |
1789 |
1000 |
1 |
20 |
10 |
1 |
0.0001706 |
0.0001885 |
0.0001719 |
0.0001815 |
0.0001763 |
0.0001706 |
0.000188 |
10 |
0.0001741 |
0 |
|||
predict |
skl |
1 |
1789 |
10000 |
1 |
20 |
10 |
1 |
0.0008564 |
0.0009719 |
0.0008614 |
0.000866 |
0.0008741 |
0.0008564 |
0.0009384 |
10 |
0.0008633 |
0 |
|||
predict_proba |
skl |
1 |
1789 |
10000 |
1 |
20 |
10 |
1 |
0.001024 |
0.001153 |
0.001031 |
0.001039 |
0.001048 |
0.001024 |
0.001119 |
10 |
0.001036 |
0 |
|||
predict |
skl |
1 |
15 |
1 |
5 |
3 |
10 |
1 |
5.292e-05 |
0.001175 |
5.47e-05 |
5.865e-05 |
0.0001685 |
5.292e-05 |
0.000826 |
10 |
5.49e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
1 |
5 |
3 |
10 |
1 |
6.795e-05 |
9.12e-05 |
7.594e-05 |
8.042e-05 |
7.777e-05 |
6.795e-05 |
8.91e-05 |
10 |
7.667e-05 |
0 |
|||
predict |
skl |
1 |
15 |
10 |
5 |
3 |
10 |
1 |
5.32e-05 |
7.052e-05 |
5.423e-05 |
5.779e-05 |
5.717e-05 |
5.32e-05 |
6.706e-05 |
10 |
5.53e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
10 |
5 |
3 |
10 |
1 |
7.357e-05 |
8.686e-05 |
7.561e-05 |
7.894e-05 |
7.801e-05 |
7.357e-05 |
8.55e-05 |
10 |
7.763e-05 |
0 |
|||
predict |
skl |
1 |
15 |
100 |
5 |
3 |
10 |
1 |
5.674e-05 |
7.766e-05 |
5.922e-05 |
6.281e-05 |
6.177e-05 |
5.674e-05 |
7.331e-05 |
10 |
5.973e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
100 |
5 |
3 |
10 |
1 |
7.456e-05 |
9.652e-05 |
7.651e-05 |
9.045e-05 |
8.22e-05 |
7.456e-05 |
9.652e-05 |
10 |
7.794e-05 |
0 |
|||
predict |
skl |
1 |
15 |
1000 |
5 |
3 |
10 |
1 |
7.456e-05 |
9.839e-05 |
7.63e-05 |
7.933e-05 |
7.935e-05 |
7.456e-05 |
9.284e-05 |
10 |
7.645e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
1000 |
5 |
3 |
10 |
1 |
0.0001086 |
0.0001261 |
0.0001104 |
0.0001154 |
0.0001133 |
0.0001086 |
0.0001239 |
10 |
0.0001112 |
0 |
|||
predict |
skl |
1 |
15 |
10000 |
5 |
3 |
10 |
1 |
0.0002396 |
0.0003907 |
0.0002431 |
0.0002456 |
0.0002603 |
0.0002396 |
0.0003466 |
10 |
0.0002445 |
0 |
|||
predict_proba |
skl |
1 |
15 |
10000 |
5 |
3 |
10 |
1 |
0.0004315 |
0.000499 |
0.0004421 |
0.0004796 |
0.0004596 |
0.0004315 |
0.000499 |
10 |
0.0004529 |
0 |
|||
predict |
skl |
1 |
425 |
1 |
5 |
10 |
10 |
1 |
5.284e-05 |
0.0009449 |
5.434e-05 |
7.079e-05 |
0.000147 |
5.284e-05 |
0.0006685 |
10 |
5.565e-05 |
0 |
|||
predict_proba |
skl |
1 |
425 |
1 |
5 |
10 |
10 |
1 |
7.217e-05 |
8.922e-05 |
7.387e-05 |
7.621e-05 |
7.616e-05 |
7.217e-05 |
8.551e-05 |
10 |
7.46e-05 |
0 |
|||
predict |
skl |
1 |
425 |
10 |
5 |
10 |
10 |
1 |
5.409e-05 |
7.19e-05 |
5.548e-05 |
6.123e-05 |
5.859e-05 |
5.409e-05 |
6.916e-05 |
10 |
5.604e-05 |
0 |
|||
predict_proba |
skl |
1 |
425 |
10 |
5 |
10 |
10 |
1 |
7.025e-05 |
8.921e-05 |
7.805e-05 |
8.277e-05 |
7.964e-05 |
7.033e-05 |
8.896e-05 |
10 |
7.882e-05 |
0 |
|||
predict |
skl |
1 |
425 |
100 |
5 |
10 |
10 |
1 |
6.121e-05 |
8.199e-05 |
6.296e-05 |
6.741e-05 |
6.639e-05 |
6.121e-05 |
7.768e-05 |
10 |
6.454e-05 |
0 |
|||
predict_proba |
skl |
1 |
425 |
100 |
5 |
10 |
10 |
1 |
7.967e-05 |
0.0001006 |
8.065e-05 |
9.506e-05 |
8.688e-05 |
7.967e-05 |
0.0001006 |
10 |
8.257e-05 |
0 |
|||
predict |
skl |
1 |
425 |
1000 |
5 |
10 |
10 |
1 |
0.0001126 |
0.0001733 |
0.0001157 |
0.0001226 |
0.0001244 |
0.0001126 |
0.0001595 |
10 |
0.0001167 |
0 |
|||
predict_proba |
skl |
1 |
425 |
1000 |
5 |
10 |
10 |
1 |
0.0001448 |
0.0002337 |
0.0001521 |
0.0001646 |
0.000163 |
0.0001448 |
0.0002117 |
10 |
0.0001547 |
0 |
|||
predict |
skl |
1 |
425 |
10000 |
5 |
10 |
10 |
1 |
0.0005919 |
0.0007505 |
0.0005967 |
0.0006039 |
0.0006137 |
0.0005919 |
0.0007035 |
10 |
0.0005973 |
0 |
|||
predict_proba |
skl |
1 |
425 |
10000 |
5 |
10 |
10 |
1 |
0.0007509 |
0.0008385 |
0.0007543 |
0.0007669 |
0.0007673 |
0.0007509 |
0.0008158 |
10 |
0.0007579 |
0 |
|||
predict |
skl |
1 |
4135 |
1 |
5 |
20 |
10 |
1 |
5.33e-05 |
0.0008578 |
5.462e-05 |
8.343e-05 |
0.0001411 |
5.33e-05 |
0.0006099 |
10 |
5.549e-05 |
0 |
|||
predict_proba |
skl |
1 |
4135 |
1 |
5 |
20 |
10 |
1 |
6.863e-05 |
9.099e-05 |
7.419e-05 |
7.941e-05 |
7.698e-05 |
6.863e-05 |
8.837e-05 |
10 |
7.526e-05 |
0 |
|||
predict |
skl |
1 |
4135 |
10 |
5 |
20 |
10 |
1 |
5.421e-05 |
7.255e-05 |
5.608e-05 |
6.132e-05 |
5.958e-05 |
5.421e-05 |
7.012e-05 |
10 |
5.828e-05 |
0 |
|||
predict_proba |
skl |
1 |
4135 |
10 |
5 |
20 |
10 |
1 |
7.153e-05 |
9.048e-05 |
7.913e-05 |
8.345e-05 |
8.079e-05 |
7.153e-05 |
9.009e-05 |
10 |
7.994e-05 |
0 |
|||
predict |
skl |
1 |
4135 |
100 |
5 |
20 |
10 |
1 |
6.871e-05 |
9.217e-05 |
7.041e-05 |
7.428e-05 |
7.402e-05 |
6.871e-05 |
8.747e-05 |
10 |
7.141e-05 |
0 |
|||
predict_proba |
skl |
1 |
4135 |
100 |
5 |
20 |
10 |
1 |
8.481e-05 |
0.0001086 |
8.72e-05 |
9.144e-05 |
9.176e-05 |
8.481e-05 |
0.0001082 |
10 |
8.832e-05 |
0 |
|||
predict |
skl |
1 |
4135 |
1000 |
5 |
20 |
10 |
1 |
0.0001577 |
0.0001942 |
0.000163 |
0.0001663 |
0.0001666 |
0.0001577 |
0.0001859 |
10 |
0.0001631 |
0 |
|||
predict_proba |
skl |
1 |
4135 |
1000 |
5 |
20 |
10 |
1 |
0.0001877 |
0.0002121 |
0.0001915 |
0.0001982 |
0.000195 |
0.0001877 |
0.0002087 |
10 |
0.0001923 |
0 |
|||
predict |
skl |
1 |
4135 |
10000 |
5 |
20 |
10 |
1 |
0.001011 |
0.001217 |
0.001017 |
0.001027 |
0.00104 |
0.001011 |
0.001156 |
10 |
0.001019 |
0 |
|||
predict_proba |
skl |
1 |
4135 |
10000 |
5 |
20 |
10 |
1 |
0.001164 |
0.001322 |
0.001169 |
0.001178 |
0.001187 |
0.001164 |
0.001276 |
10 |
0.001172 |
0 |
|||
predict |
skl |
1 |
13 |
1 |
10 |
3 |
10 |
1 |
5.26e-05 |
0.0008869 |
5.413e-05 |
6.826e-05 |
0.0001496 |
5.26e-05 |
0.000635 |
10 |
5.539e-05 |
0 |
|||
predict_proba |
skl |
1 |
13 |
1 |
10 |
3 |
10 |
1 |
7.195e-05 |
8.85e-05 |
7.333e-05 |
7.948e-05 |
7.67e-05 |
7.195e-05 |
8.711e-05 |
10 |
7.42e-05 |
0 |
|||
predict |
skl |
1 |
13 |
10 |
10 |
3 |
10 |
1 |
5.347e-05 |
7.052e-05 |
5.465e-05 |
5.933e-05 |
5.772e-05 |
5.347e-05 |
6.755e-05 |
10 |
5.538e-05 |
0 |
|||
predict_proba |
skl |
1 |
13 |
10 |
10 |
3 |
10 |
1 |
7.432e-05 |
8.88e-05 |
7.527e-05 |
8.197e-05 |
7.881e-05 |
7.432e-05 |
8.88e-05 |
10 |
7.613e-05 |
0 |
|||
predict |
skl |
1 |
13 |
100 |
10 |
3 |
10 |
1 |
5.708e-05 |
7.787e-05 |
5.83e-05 |
6.58e-05 |
6.235e-05 |
5.708e-05 |
7.453e-05 |
10 |
5.934e-05 |
0 |
|||
predict_proba |
skl |
1 |
13 |
100 |
10 |
3 |
10 |
1 |
7.47e-05 |
9.538e-05 |
7.765e-05 |
9.002e-05 |
8.24e-05 |
7.47e-05 |
9.538e-05 |
10 |
7.85e-05 |
0 |
|||
predict |
skl |
1 |
13 |
1000 |
10 |
3 |
10 |
1 |
7.868e-05 |
0.0001034 |
7.981e-05 |
8.422e-05 |
8.366e-05 |
7.868e-05 |
9.765e-05 |
10 |
8.092e-05 |
0 |
|||
predict_proba |
skl |
1 |
13 |
1000 |
10 |
3 |
10 |
1 |
0.0001119 |
0.0001293 |
0.0001139 |
0.0001199 |
0.0001172 |
0.0001119 |
0.0001276 |
10 |
0.0001155 |
0 |
|||
predict |
skl |
1 |
13 |
10000 |
10 |
3 |
10 |
1 |
0.0002845 |
0.0004842 |
0.0002933 |
0.0003053 |
0.000315 |
0.0002845 |
0.0004268 |
10 |
0.0002969 |
0 |
|||
predict_proba |
skl |
1 |
13 |
10000 |
10 |
3 |
10 |
1 |
0.0004704 |
0.0005528 |
0.0004757 |
0.0004956 |
0.0004922 |
0.0004704 |
0.0005433 |
10 |
0.0004819 |
0 |
|||
predict |
skl |
1 |
437 |
1 |
10 |
10 |
10 |
1 |
5.319e-05 |
0.0009195 |
5.392e-05 |
5.752e-05 |
0.0001427 |
5.319e-05 |
0.0006503 |
10 |
5.52e-05 |
0 |
|||
predict_proba |
skl |
1 |
437 |
1 |
10 |
10 |
10 |
1 |
7.298e-05 |
9.082e-05 |
7.578e-05 |
7.759e-05 |
7.746e-05 |
7.298e-05 |
8.718e-05 |
10 |
7.63e-05 |
0 |
|||
predict |
skl |
1 |
437 |
10 |
10 |
10 |
10 |
1 |
5.419e-05 |
8.115e-05 |
5.593e-05 |
6.019e-05 |
5.966e-05 |
5.419e-05 |
7.456e-05 |
10 |
5.706e-05 |
0 |
|||
predict_proba |
skl |
1 |
437 |
10 |
10 |
10 |
10 |
1 |
7.489e-05 |
8.784e-05 |
7.715e-05 |
8.113e-05 |
7.906e-05 |
7.489e-05 |
8.669e-05 |
10 |
7.811e-05 |
0 |
|||
predict |
skl |
1 |
437 |
100 |
10 |
10 |
10 |
1 |
6.117e-05 |
8.341e-05 |
6.211e-05 |
6.864e-05 |
6.655e-05 |
6.117e-05 |
7.933e-05 |
10 |
6.403e-05 |
0 |
|||
predict_proba |
skl |
1 |
437 |
100 |
10 |
10 |
10 |
1 |
7.903e-05 |
0.0001013 |
8.268e-05 |
9.528e-05 |
8.739e-05 |
7.903e-05 |
0.0001013 |
10 |
8.388e-05 |
0 |
|||
predict |
skl |
1 |
437 |
1000 |
10 |
10 |
10 |
1 |
0.0001171 |
0.0001428 |
0.0001186 |
0.0001261 |
0.0001233 |
0.0001171 |
0.0001384 |
10 |
0.0001202 |
0 |
|||
predict_proba |
skl |
1 |
437 |
1000 |
10 |
10 |
10 |
1 |
0.0001463 |
0.0001632 |
0.0001479 |
0.0001537 |
0.0001514 |
0.0001463 |
0.0001617 |
10 |
0.0001499 |
0 |
|||
predict |
skl |
1 |
437 |
10000 |
10 |
10 |
10 |
1 |
0.0006343 |
0.0008405 |
0.0006449 |
0.0006562 |
0.0006659 |
0.0006343 |
0.0007811 |
10 |
0.0006473 |
0 |
|||
predict_proba |
skl |
1 |
437 |
10000 |
10 |
10 |
10 |
1 |
0.0007982 |
0.0008875 |
0.0008034 |
0.0008155 |
0.0008159 |
0.0007982 |
0.0008643 |
10 |
0.0008104 |
0 |
|||
predict |
skl |
1 |
3081 |
1 |
10 |
20 |
10 |
1 |
5.294e-05 |
0.0009092 |
5.428e-05 |
5.786e-05 |
0.0001416 |
5.294e-05 |
0.0006432 |
10 |
5.435e-05 |
0 |
|||
predict_proba |
skl |
1 |
3081 |
1 |
10 |
20 |
10 |
1 |
6.816e-05 |
9.003e-05 |
7.465e-05 |
8.022e-05 |
7.701e-05 |
6.816e-05 |
8.854e-05 |
10 |
7.511e-05 |
0 |
|||
predict |
skl |
1 |
3081 |
10 |
10 |
20 |
10 |
1 |
5.409e-05 |
7.246e-05 |
5.563e-05 |
6.031e-05 |
5.895e-05 |
5.409e-05 |
6.927e-05 |
10 |
5.733e-05 |
0 |
|||
predict_proba |
skl |
1 |
3081 |
10 |
10 |
20 |
10 |
1 |
7.546e-05 |
8.918e-05 |
7.915e-05 |
8.213e-05 |
8.042e-05 |
7.546e-05 |
8.809e-05 |
10 |
8.015e-05 |
0 |
|||
predict |
skl |
1 |
3081 |
100 |
10 |
20 |
10 |
1 |
6.591e-05 |
8.773e-05 |
6.783e-05 |
7.412e-05 |
7.181e-05 |
6.591e-05 |
8.418e-05 |
10 |
7.002e-05 |
0 |
|||
predict_proba |
skl |
1 |
3081 |
100 |
10 |
20 |
10 |
1 |
8.47e-05 |
0.000106 |
8.768e-05 |
9.222e-05 |
9.149e-05 |
8.47e-05 |
0.0001059 |
10 |
8.858e-05 |
0 |
|||
predict |
skl |
1 |
3081 |
1000 |
10 |
20 |
10 |
1 |
0.0001559 |
0.0001895 |
0.0001574 |
0.000163 |
0.0001631 |
0.0001559 |
0.0001823 |
10 |
0.000159 |
0 |
|||
predict_proba |
skl |
1 |
3081 |
1000 |
10 |
20 |
10 |
1 |
0.000185 |
0.0002052 |
0.0001876 |
0.0001916 |
0.0001908 |
0.000185 |
0.0002022 |
10 |
0.0001884 |
0 |
|||
predict |
skl |
1 |
3081 |
10000 |
10 |
20 |
10 |
1 |
0.000999 |
0.001241 |
0.001008 |
0.001013 |
0.001034 |
0.000999 |
0.001171 |
10 |
0.001012 |
0 |
|||
predict_proba |
skl |
1 |
3081 |
10000 |
10 |
20 |
10 |
1 |
0.001157 |
0.001276 |
0.001164 |
0.001188 |
0.00118 |
0.001157 |
0.001247 |
10 |
0.001167 |
0 |
|||
predict |
skl |
1 |
11 |
1 |
20 |
3 |
10 |
1 |
5.488e-05 |
0.0008657 |
5.685e-05 |
0.0001046 |
0.0001505 |
5.488e-05 |
0.0006201 |
10 |
5.891e-05 |
0 |
|||
predict_proba |
skl |
1 |
11 |
1 |
20 |
3 |
10 |
1 |
6.813e-05 |
9.105e-05 |
7.459e-05 |
8.356e-05 |
7.872e-05 |
6.813e-05 |
9.105e-05 |
10 |
7.712e-05 |
0 |
|||
predict |
skl |
1 |
11 |
10 |
20 |
3 |
10 |
1 |
5.37e-05 |
7.114e-05 |
5.448e-05 |
5.919e-05 |
5.77e-05 |
5.37e-05 |
6.822e-05 |
10 |
5.505e-05 |
0 |
|||
predict_proba |
skl |
1 |
11 |
10 |
20 |
3 |
10 |
1 |
7.005e-05 |
8.895e-05 |
7.856e-05 |
8.322e-05 |
7.977e-05 |
7.024e-05 |
8.895e-05 |
10 |
7.929e-05 |
0 |
|||
predict |
skl |
1 |
11 |
100 |
20 |
3 |
10 |
1 |
5.77e-05 |
7.95e-05 |
5.909e-05 |
6.387e-05 |
6.27e-05 |
5.77e-05 |
7.486e-05 |
10 |
6.076e-05 |
0 |
|||
predict_proba |
skl |
1 |
11 |
100 |
20 |
3 |
10 |
1 |
7.573e-05 |
9.716e-05 |
7.811e-05 |
9.182e-05 |
8.359e-05 |
7.573e-05 |
9.716e-05 |
10 |
7.963e-05 |
0 |
|||
predict |
skl |
1 |
11 |
1000 |
20 |
3 |
10 |
1 |
8.351e-05 |
0.0001122 |
8.481e-05 |
8.833e-05 |
8.889e-05 |
8.351e-05 |
0.0001051 |
10 |
8.588e-05 |
0 |
|||
predict_proba |
skl |
1 |
11 |
1000 |
20 |
3 |
10 |
1 |
0.0001175 |
0.000135 |
0.0001196 |
0.0001233 |
0.0001224 |
0.0001175 |
0.0001325 |
10 |
0.0001209 |
0 |
|||
predict |
skl |
1 |
11 |
10000 |
20 |
3 |
10 |
1 |
0.0003343 |
0.0006069 |
0.0003393 |
0.000371 |
0.0003828 |
0.0003343 |
0.0005377 |
10 |
0.0003557 |
0 |
|||
predict_proba |
skl |
1 |
11 |
10000 |
20 |
3 |
10 |
1 |
0.0005312 |
0.0006649 |
0.0005491 |
0.000571 |
0.0005704 |
0.0005312 |
0.0006495 |
10 |
0.0005583 |
0 |
|||
predict |
skl |
1 |
377 |
1 |
20 |
10 |
10 |
1 |
5.423e-05 |
0.0008509 |
5.674e-05 |
6.538e-05 |
0.0001419 |
5.423e-05 |
0.000606 |
10 |
5.724e-05 |
0 |
|||
predict_proba |
skl |
1 |
377 |
1 |
20 |
10 |
10 |
1 |
6.751e-05 |
8.989e-05 |
7.402e-05 |
8.403e-05 |
7.842e-05 |
6.751e-05 |
8.989e-05 |
10 |
7.624e-05 |
0 |
|||
predict |
skl |
1 |
377 |
10 |
20 |
10 |
10 |
1 |
5.422e-05 |
7.151e-05 |
5.575e-05 |
6.147e-05 |
5.922e-05 |
5.422e-05 |
6.93e-05 |
10 |
5.764e-05 |
0 |
|||
predict_proba |
skl |
1 |
377 |
10 |
20 |
10 |
10 |
1 |
7.422e-05 |
8.869e-05 |
7.555e-05 |
7.981e-05 |
7.825e-05 |
7.422e-05 |
8.678e-05 |
10 |
7.657e-05 |
0 |
|||
predict |
skl |
1 |
377 |
100 |
20 |
10 |
10 |
1 |
6.256e-05 |
8.301e-05 |
6.455e-05 |
6.811e-05 |
6.752e-05 |
6.256e-05 |
7.891e-05 |
10 |
6.563e-05 |
0 |
|||
predict_proba |
skl |
1 |
377 |
100 |
20 |
10 |
10 |
1 |
8.009e-05 |
0.0001007 |
8.191e-05 |
9.576e-05 |
8.713e-05 |
8.009e-05 |
0.0001007 |
10 |
8.361e-05 |
0 |
|||
predict |
skl |
1 |
377 |
1000 |
20 |
10 |
10 |
1 |
0.0001224 |
0.0001552 |
0.0001252 |
0.000129 |
0.0001291 |
0.0001224 |
0.000147 |
10 |
0.0001259 |
0 |
|||
predict_proba |
skl |
1 |
377 |
1000 |
20 |
10 |
10 |
1 |
0.0001516 |
0.0001748 |
0.0001546 |
0.0001574 |
0.0001575 |
0.0001516 |
0.0001704 |
10 |
0.0001548 |
0 |
|||
predict |
skl |
1 |
377 |
10000 |
20 |
10 |
10 |
1 |
0.0006952 |
0.0009556 |
0.0007033 |
0.0007261 |
0.0007357 |
0.0006952 |
0.0008824 |
10 |
0.0007097 |
0 |
|||
predict_proba |
skl |
1 |
377 |
10000 |
20 |
10 |
10 |
1 |
0.0008436 |
0.0009648 |
0.0008506 |
0.00087 |
0.0008705 |
0.0008436 |
0.0009455 |
10 |
0.0008536 |
0 |
|||
predict |
skl |
1 |
4983 |
1 |
20 |
20 |
10 |
1 |
5.382e-05 |
0.0009021 |
5.484e-05 |
7.026e-05 |
0.0001453 |
5.382e-05 |
0.0006403 |
10 |
5.574e-05 |
0 |
|||
predict_proba |
skl |
1 |
4983 |
1 |
20 |
20 |
10 |
1 |
6.894e-05 |
9.178e-05 |
7.698e-05 |
8.039e-05 |
7.877e-05 |
6.894e-05 |
8.985e-05 |
10 |
7.82e-05 |
0 |
|||
predict |
skl |
1 |
4983 |
10 |
20 |
20 |
10 |
1 |
5.633e-05 |
7.322e-05 |
5.876e-05 |
6.154e-05 |
6.094e-05 |
5.633e-05 |
7.022e-05 |
10 |
5.913e-05 |
0 |
|||
predict_proba |
skl |
1 |
4983 |
10 |
20 |
20 |
10 |
1 |
7.095e-05 |
8.948e-05 |
7.748e-05 |
8.403e-05 |
8.039e-05 |
7.095e-05 |
8.948e-05 |
10 |
7.932e-05 |
0 |
|||
predict |
skl |
1 |
4983 |
100 |
20 |
20 |
10 |
1 |
7.139e-05 |
9.34e-05 |
7.279e-05 |
7.852e-05 |
7.685e-05 |
7.139e-05 |
8.957e-05 |
10 |
7.437e-05 |
0 |
|||
predict_proba |
skl |
1 |
4983 |
100 |
20 |
20 |
10 |
1 |
8.838e-05 |
0.0001191 |
8.912e-05 |
9.66e-05 |
9.553e-05 |
8.838e-05 |
0.0001147 |
10 |
9.092e-05 |
0 |
|||
predict |
skl |
1 |
4983 |
1000 |
20 |
20 |
10 |
1 |
0.0001753 |
0.0002165 |
0.0001777 |
0.0001853 |
0.0001842 |
0.0001753 |
0.0002075 |
10 |
0.0001796 |
0 |
|||
predict_proba |
skl |
1 |
4983 |
1000 |
20 |
20 |
10 |
1 |
0.0002038 |
0.000235 |
0.0002066 |
0.0002116 |
0.0002116 |
0.0002038 |
0.0002286 |
10 |
0.0002092 |
0 |
|||
predict |
skl |
1 |
4983 |
10000 |
20 |
20 |
10 |
1 |
0.00119 |
0.001511 |
0.0012 |
0.001228 |
0.001238 |
0.00119 |
0.001419 |
10 |
0.001204 |
0 |
|||
predict_proba |
skl |
1 |
4983 |
10000 |
20 |
20 |
10 |
1 |
0.001341 |
0.001517 |
0.001354 |
0.00138 |
0.001378 |
0.001341 |
0.001475 |
10 |
0.001359 |
0 |
|||
predict |
skl |
1 |
15 |
1 |
50 |
3 |
10 |
1 |
5.354e-05 |
0.0009037 |
5.611e-05 |
6.39e-05 |
0.0001466 |
5.354e-05 |
0.0006421 |
10 |
5.692e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
1 |
50 |
3 |
10 |
1 |
6.921e-05 |
9.152e-05 |
7.492e-05 |
8.046e-05 |
7.764e-05 |
6.921e-05 |
8.877e-05 |
10 |
7.596e-05 |
0 |
|||
predict |
skl |
1 |
15 |
10 |
50 |
3 |
10 |
1 |
5.415e-05 |
7.578e-05 |
5.531e-05 |
6.039e-05 |
5.881e-05 |
5.415e-05 |
7.129e-05 |
10 |
5.567e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
10 |
50 |
3 |
10 |
1 |
7.188e-05 |
8.997e-05 |
7.971e-05 |
8.307e-05 |
8.113e-05 |
7.225e-05 |
8.997e-05 |
10 |
8.086e-05 |
0 |
|||
predict |
skl |
1 |
15 |
100 |
50 |
3 |
10 |
1 |
6.002e-05 |
8.12e-05 |
6.123e-05 |
6.662e-05 |
6.475e-05 |
6.002e-05 |
7.697e-05 |
10 |
6.223e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
100 |
50 |
3 |
10 |
1 |
7.745e-05 |
9.868e-05 |
7.968e-05 |
9.292e-05 |
8.504e-05 |
7.745e-05 |
9.868e-05 |
10 |
8.093e-05 |
0 |
|||
predict |
skl |
1 |
15 |
1000 |
50 |
3 |
10 |
1 |
9.984e-05 |
0.0001624 |
0.0001033 |
0.0001109 |
0.000111 |
9.984e-05 |
0.0001461 |
10 |
0.0001045 |
0 |
|||
predict_proba |
skl |
1 |
15 |
1000 |
50 |
3 |
10 |
1 |
0.0001333 |
0.0001635 |
0.0001353 |
0.0001448 |
0.0001407 |
0.0001333 |
0.0001583 |
10 |
0.0001372 |
0 |
|||
predict |
skl |
1 |
15 |
10000 |
50 |
3 |
10 |
1 |
0.0005304 |
0.0008688 |
0.0005389 |
0.0005818 |
0.0005875 |
0.0005304 |
0.0007785 |
10 |
0.0005501 |
0 |
|||
predict_proba |
skl |
1 |
15 |
10000 |
50 |
3 |
10 |
1 |
0.0007382 |
0.0009159 |
0.0007492 |
0.000791 |
0.0007826 |
0.0007382 |
0.0008829 |
10 |
0.0007658 |
0 |
|||
predict |
skl |
1 |
397 |
1 |
50 |
10 |
10 |
1 |
5.281e-05 |
0.0009176 |
5.412e-05 |
6.862e-05 |
0.0001456 |
5.281e-05 |
0.0006503 |
10 |
5.549e-05 |
0 |
|||
predict_proba |
skl |
1 |
397 |
1 |
50 |
10 |
10 |
1 |
6.809e-05 |
9.254e-05 |
7.504e-05 |
8.115e-05 |
7.842e-05 |
6.809e-05 |
9.236e-05 |
10 |
7.558e-05 |
0 |
|||
predict |
skl |
1 |
397 |
10 |
50 |
10 |
10 |
1 |
5.573e-05 |
7.509e-05 |
5.702e-05 |
6.065e-05 |
5.997e-05 |
5.573e-05 |
7.1e-05 |
10 |
5.753e-05 |
0 |
|||
predict_proba |
skl |
1 |
397 |
10 |
50 |
10 |
10 |
1 |
7.201e-05 |
9.154e-05 |
8.026e-05 |
8.336e-05 |
8.181e-05 |
7.223e-05 |
9.139e-05 |
10 |
8.206e-05 |
0 |
|||
predict |
skl |
1 |
397 |
100 |
50 |
10 |
10 |
1 |
6.38e-05 |
8.467e-05 |
6.5e-05 |
6.969e-05 |
6.837e-05 |
6.38e-05 |
8.053e-05 |
10 |
6.524e-05 |
0 |
|||
predict_proba |
skl |
1 |
397 |
100 |
50 |
10 |
10 |
1 |
8.205e-05 |
0.0001034 |
8.511e-05 |
9.814e-05 |
8.987e-05 |
8.205e-05 |
0.0001034 |
10 |
8.712e-05 |
0 |
|||
predict |
skl |
1 |
397 |
1000 |
50 |
10 |
10 |
1 |
0.000139 |
0.0001943 |
0.000141 |
0.0001474 |
0.0001482 |
0.000139 |
0.0001792 |
10 |
0.0001424 |
0 |
|||
predict_proba |
skl |
1 |
397 |
1000 |
50 |
10 |
10 |
1 |
0.0001688 |
0.0002034 |
0.0001708 |
0.0001769 |
0.0001761 |
0.0001688 |
0.0001954 |
10 |
0.0001725 |
0 |
|||
predict |
skl |
1 |
397 |
10000 |
50 |
10 |
10 |
1 |
0.000883 |
0.00129 |
0.0009005 |
0.0009309 |
0.0009479 |
0.000883 |
0.001176 |
10 |
0.0009082 |
0 |
|||
predict_proba |
skl |
1 |
397 |
10000 |
50 |
10 |
10 |
1 |
0.001054 |
0.001234 |
0.001078 |
0.001108 |
0.001097 |
0.001054 |
0.001194 |
10 |
0.001081 |
0 |
|||
predict |
skl |
1 |
8635 |
1 |
50 |
20 |
10 |
1 |
5.312e-05 |
0.0009152 |
5.492e-05 |
5.975e-05 |
0.000143 |
5.312e-05 |
0.0006476 |
10 |
5.583e-05 |
0 |
|||
predict_proba |
skl |
1 |
8635 |
1 |
50 |
20 |
10 |
1 |
6.967e-05 |
9.251e-05 |
7.594e-05 |
8.118e-05 |
7.834e-05 |
6.967e-05 |
8.952e-05 |
10 |
7.659e-05 |
0 |
|||
predict |
skl |
1 |
8635 |
10 |
50 |
20 |
10 |
1 |
5.687e-05 |
7.798e-05 |
5.916e-05 |
6.329e-05 |
6.234e-05 |
5.687e-05 |
7.39e-05 |
10 |
6.032e-05 |
0 |
|||
predict_proba |
skl |
1 |
8635 |
10 |
50 |
20 |
10 |
1 |
7.259e-05 |
9.315e-05 |
8.118e-05 |
8.478e-05 |
8.27e-05 |
7.259e-05 |
9.285e-05 |
10 |
8.262e-05 |
0 |
|||
predict |
skl |
1 |
8635 |
100 |
50 |
20 |
10 |
1 |
7.555e-05 |
0.0001027 |
7.789e-05 |
8.159e-05 |
8.226e-05 |
7.555e-05 |
9.713e-05 |
10 |
8.044e-05 |
0 |
|||
predict_proba |
skl |
1 |
8635 |
100 |
50 |
20 |
10 |
1 |
9.303e-05 |
0.0001099 |
9.515e-05 |
9.814e-05 |
9.778e-05 |
9.303e-05 |
0.000107 |
10 |
9.601e-05 |
0 |
|||
predict |
skl |
1 |
8635 |
1000 |
50 |
20 |
10 |
1 |
0.00021 |
0.0003139 |
0.0002184 |
0.0002247 |
0.0002296 |
0.00021 |
0.0002861 |
10 |
0.0002198 |
0 |
|||
predict_proba |
skl |
1 |
8635 |
1000 |
50 |
20 |
10 |
1 |
0.0002434 |
0.0003252 |
0.0002516 |
0.0002578 |
0.0002612 |
0.0002434 |
0.0003045 |
10 |
0.000256 |
0 |
|||
predict |
skl |
1 |
8635 |
10000 |
50 |
20 |
10 |
1 |
0.001608 |
0.002072 |
0.001624 |
0.001663 |
0.001679 |
0.001608 |
0.001939 |
10 |
0.001634 |
0 |
|||
predict_proba |
skl |
1 |
8635 |
10000 |
50 |
20 |
10 |
1 |
0.001782 |
0.002046 |
0.0018 |
0.001818 |
0.001833 |
0.001782 |
0.00198 |
10 |
0.001809 |
0 |
|||
predict |
skl |
1 |
15 |
1 |
100 |
3 |
10 |
1 |
5.465e-05 |
0.000895 |
5.694e-05 |
0.0001069 |
0.0001592 |
5.465e-05 |
0.0006459 |
10 |
5.872e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
1 |
100 |
3 |
10 |
1 |
6.839e-05 |
9.089e-05 |
7.371e-05 |
7.868e-05 |
7.669e-05 |
6.839e-05 |
8.805e-05 |
10 |
7.474e-05 |
0 |
|||
predict |
skl |
1 |
15 |
10 |
100 |
3 |
10 |
1 |
5.448e-05 |
7.643e-05 |
5.543e-05 |
6.146e-05 |
5.959e-05 |
5.448e-05 |
7.215e-05 |
10 |
5.701e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
10 |
100 |
3 |
10 |
1 |
7.626e-05 |
9.541e-05 |
7.8e-05 |
8.336e-05 |
8.105e-05 |
7.626e-05 |
9.148e-05 |
10 |
7.932e-05 |
0 |
|||
predict |
skl |
1 |
15 |
100 |
100 |
3 |
10 |
1 |
6.222e-05 |
8.548e-05 |
6.371e-05 |
6.74e-05 |
6.691e-05 |
6.222e-05 |
7.99e-05 |
10 |
6.415e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
100 |
100 |
3 |
10 |
1 |
8.121e-05 |
0.0001025 |
8.341e-05 |
9.567e-05 |
8.833e-05 |
8.121e-05 |
0.0001025 |
10 |
8.494e-05 |
0 |
|||
predict |
skl |
1 |
15 |
1000 |
100 |
3 |
10 |
1 |
0.0001303 |
0.0002897 |
0.0001392 |
0.0001679 |
0.0001629 |
0.0001303 |
0.0002531 |
10 |
0.0001437 |
0 |
|||
predict_proba |
skl |
1 |
15 |
1000 |
100 |
3 |
10 |
1 |
0.0001654 |
0.0002325 |
0.0001711 |
0.0001842 |
0.0001813 |
0.0001654 |
0.0002192 |
10 |
0.0001731 |
0 |
|||
predict |
skl |
1 |
15 |
10000 |
100 |
3 |
10 |
1 |
0.001038 |
0.001308 |
0.001054 |
0.001069 |
0.001085 |
0.001038 |
0.001236 |
10 |
0.00106 |
0 |
|||
predict_proba |
skl |
1 |
15 |
10000 |
100 |
3 |
10 |
1 |
0.00122 |
0.001485 |
0.001229 |
0.001289 |
0.001275 |
0.00122 |
0.001428 |
10 |
0.001241 |
0 |
|||
predict |
skl |
1 |
547 |
1 |
100 |
10 |
10 |
1 |
5.258e-05 |
0.0007949 |
5.391e-05 |
8.539e-05 |
0.0001356 |
5.258e-05 |
0.0005672 |
10 |
5.518e-05 |
0 |
|||
predict_proba |
skl |
1 |
547 |
1 |
100 |
10 |
10 |
1 |
6.814e-05 |
9.12e-05 |
7.547e-05 |
7.954e-05 |
7.743e-05 |
6.814e-05 |
8.844e-05 |
10 |
7.612e-05 |
0 |
|||
predict |
skl |
1 |
547 |
10 |
100 |
10 |
10 |
1 |
5.518e-05 |
7.512e-05 |
5.702e-05 |
6.062e-05 |
5.993e-05 |
5.518e-05 |
7.106e-05 |
10 |
5.785e-05 |
0 |
|||
predict_proba |
skl |
1 |
547 |
10 |
100 |
10 |
10 |
1 |
7.097e-05 |
9.008e-05 |
7.77e-05 |
8.267e-05 |
8.027e-05 |
7.097e-05 |
8.999e-05 |
10 |
8.014e-05 |
0 |
|||
predict |
skl |
1 |
547 |
100 |
100 |
10 |
10 |
1 |
6.767e-05 |
8.757e-05 |
6.823e-05 |
7.201e-05 |
7.14e-05 |
6.767e-05 |
8.279e-05 |
10 |
6.907e-05 |
0 |
|||
predict_proba |
skl |
1 |
547 |
100 |
100 |
10 |
10 |
1 |
8.427e-05 |
0.0001072 |
8.775e-05 |
0.0001003 |
9.193e-05 |
8.427e-05 |
0.0001067 |
10 |
8.907e-05 |
0 |
|||
predict |
skl |
1 |
547 |
1000 |
100 |
10 |
10 |
1 |
0.0001663 |
0.0003433 |
0.0001769 |
0.0001876 |
0.0001946 |
0.0001663 |
0.0002931 |
10 |
0.0001787 |
0 |
|||
predict_proba |
skl |
1 |
547 |
1000 |
100 |
10 |
10 |
1 |
0.0002 |
0.0002753 |
0.0002066 |
0.0002194 |
0.0002165 |
0.0002 |
0.0002583 |
10 |
0.000208 |
0 |
|||
predict |
skl |
1 |
547 |
10000 |
100 |
10 |
10 |
1 |
0.00134 |
0.001624 |
0.001351 |
0.001378 |
0.00139 |
0.00134 |
0.001548 |
10 |
0.001368 |
0 |
|||
predict_proba |
skl |
1 |
547 |
10000 |
100 |
10 |
10 |
1 |
0.001484 |
0.001762 |
0.001524 |
0.00154 |
0.00155 |
0.001484 |
0.001697 |
10 |
0.001528 |
0 |
|||
predict |
skl |
1 |
3809 |
1 |
100 |
20 |
10 |
1 |
5.319e-05 |
0.0007461 |
5.459e-05 |
7.082e-05 |
0.0001292 |
5.319e-05 |
0.0005328 |
10 |
5.574e-05 |
0 |
|||
predict_proba |
skl |
1 |
3809 |
1 |
100 |
20 |
10 |
1 |
6.804e-05 |
9.154e-05 |
7.57e-05 |
7.957e-05 |
7.783e-05 |
6.804e-05 |
8.915e-05 |
10 |
7.69e-05 |
0 |
|||
predict |
skl |
1 |
3809 |
10 |
100 |
20 |
10 |
1 |
5.722e-05 |
7.761e-05 |
5.978e-05 |
6.387e-05 |
6.247e-05 |
5.722e-05 |
7.365e-05 |
10 |
6.017e-05 |
0 |
|||
predict_proba |
skl |
1 |
3809 |
10 |
100 |
20 |
10 |
1 |
7.805e-05 |
9.177e-05 |
7.929e-05 |
8.413e-05 |
8.202e-05 |
7.805e-05 |
9.005e-05 |
10 |
8.063e-05 |
0 |
|||
predict |
skl |
1 |
3809 |
100 |
100 |
20 |
10 |
1 |
7.476e-05 |
9.834e-05 |
7.634e-05 |
8.368e-05 |
8.142e-05 |
7.476e-05 |
9.634e-05 |
10 |
7.815e-05 |
0 |
|||
predict_proba |
skl |
1 |
3809 |
100 |
100 |
20 |
10 |
1 |
9.319e-05 |
0.0001208 |
9.456e-05 |
0.0001008 |
9.939e-05 |
9.319e-05 |
0.0001148 |
10 |
9.655e-05 |
0 |
|||
predict |
skl |
1 |
3809 |
1000 |
100 |
20 |
10 |
1 |
0.000224 |
0.0003741 |
0.0002306 |
0.0002425 |
0.0002489 |
0.000224 |
0.0003324 |
10 |
0.0002353 |
0 |
|||
predict_proba |
skl |
1 |
3809 |
1000 |
100 |
20 |
10 |
1 |
0.0002581 |
0.0003678 |
0.0002622 |
0.0002726 |
0.0002755 |
0.0002581 |
0.0003369 |
10 |
0.0002644 |
0 |
|||
predict |
skl |
1 |
3809 |
10000 |
100 |
20 |
10 |
1 |
0.001896 |
0.00219 |
0.001923 |
0.001946 |
0.001948 |
0.001896 |
0.00211 |
10 |
0.001924 |
0 |
|||
predict_proba |
skl |
1 |
3809 |
10000 |
100 |
20 |
10 |
1 |
0.00204 |
0.002373 |
0.002054 |
0.002086 |
0.002096 |
0.00204 |
0.002281 |
10 |
0.002061 |
0 |
|||
predict |
skl |
1 |
15 |
1 |
200 |
3 |
10 |
1 |
5.214e-05 |
0.0007235 |
5.338e-05 |
5.75e-05 |
0.0001223 |
5.214e-05 |
0.0005152 |
10 |
5.389e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
1 |
200 |
3 |
10 |
1 |
7.341e-05 |
9.183e-05 |
7.595e-05 |
8.05e-05 |
7.861e-05 |
7.341e-05 |
8.836e-05 |
10 |
7.676e-05 |
0 |
|||
predict |
skl |
1 |
15 |
10 |
200 |
3 |
10 |
1 |
5.534e-05 |
7.586e-05 |
5.734e-05 |
6.117e-05 |
6.01e-05 |
5.534e-05 |
7.155e-05 |
10 |
5.808e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
10 |
200 |
3 |
10 |
1 |
7.106e-05 |
9.029e-05 |
7.71e-05 |
8.253e-05 |
7.961e-05 |
7.106e-05 |
8.943e-05 |
10 |
7.842e-05 |
0 |
|||
predict |
skl |
1 |
15 |
100 |
200 |
3 |
10 |
1 |
6.846e-05 |
9.021e-05 |
7.045e-05 |
7.31e-05 |
7.298e-05 |
6.846e-05 |
8.503e-05 |
10 |
7.054e-05 |
0 |
|||
predict_proba |
skl |
1 |
15 |
100 |
200 |
3 |
10 |
1 |
8.587e-05 |
0.0001107 |
8.881e-05 |
9.322e-05 |
9.324e-05 |
8.587e-05 |
0.0001092 |
10 |
9.075e-05 |
0 |
|||
predict |
skl |
1 |
15 |
1000 |
200 |
3 |
10 |
1 |
0.0002069 |
0.0004092 |
0.0002127 |
0.0002322 |
0.0002399 |
0.0002069 |
0.0003528 |
10 |
0.0002231 |
0 |
|||
predict_proba |
skl |
1 |
15 |
1000 |
200 |
3 |
10 |
1 |
0.0002403 |
0.0003105 |
0.0002446 |
0.0002563 |
0.0002549 |
0.0002403 |
0.0002937 |
10 |
0.0002491 |
0 |
|||
predict |
skl |
1 |
15 |
10000 |
200 |
3 |
10 |
1 |
0.002065 |
0.002412 |
0.002099 |
0.002201 |
0.002164 |
0.002065 |
0.002358 |
10 |
0.002148 |
0 |
|||
predict_proba |
skl |
1 |
15 |
10000 |
200 |
3 |
10 |
1 |
0.002244 |
0.002458 |
0.002276 |
0.002309 |
0.002302 |
0.002244 |
0.002416 |
10 |
0.002288 |
0 |
|||
predict |
skl |
1 |
685 |
1 |
200 |
10 |
10 |
1 |
5.328e-05 |
0.0007181 |
5.398e-05 |
6.696e-05 |
0.0001237 |
5.328e-05 |
0.0005121 |
10 |
5.571e-05 |
0 |
|||
predict_proba |
skl |
1 |
685 |
1 |
200 |
10 |
10 |
1 |
7.182e-05 |
8.843e-05 |
7.311e-05 |
7.645e-05 |
7.603e-05 |
7.182e-05 |
8.516e-05 |
10 |
7.486e-05 |
0 |
|||
predict |
skl |
1 |
685 |
10 |
200 |
10 |
10 |
1 |
5.615e-05 |
7.806e-05 |
5.725e-05 |
6.306e-05 |
6.142e-05 |
5.615e-05 |
7.41e-05 |
10 |
5.899e-05 |
0 |
|||
predict_proba |
skl |
1 |
685 |
10 |
200 |
10 |
10 |
1 |
7.143e-05 |
9.124e-05 |
7.91e-05 |
8.331e-05 |
8.097e-05 |
7.143e-05 |
9.076e-05 |
10 |
8.061e-05 |
0 |
|||
predict |
skl |
1 |
685 |
100 |
200 |
10 |
10 |
1 |
7.32e-05 |
9.361e-05 |
7.466e-05 |
8.292e-05 |
7.836e-05 |
7.32e-05 |
9.087e-05 |
10 |
7.525e-05 |
0 |
|||
predict_proba |
skl |
1 |
685 |
100 |
200 |
10 |
10 |
1 |
9.059e-05 |
0.0001124 |
9.519e-05 |
9.766e-05 |
9.793e-05 |
9.059e-05 |
0.0001121 |
10 |
9.56e-05 |
0 |
|||
predict |
skl |
1 |
685 |
1000 |
200 |
10 |
10 |
1 |
0.0002379 |
0.00045 |
0.0002582 |
0.0002671 |
0.0002766 |
0.0002379 |
0.0003922 |
10 |
0.000261 |
0 |
|||
predict_proba |
skl |
1 |
685 |
1000 |
200 |
10 |
10 |
1 |
0.0002693 |
0.0003504 |
0.000274 |
0.0002802 |
0.0002833 |
0.0002693 |
0.000328 |
10 |
0.0002756 |
0 |
|||
predict |
skl |
1 |
685 |
10000 |
200 |
10 |
10 |
1 |
0.002408 |
0.002732 |
0.002468 |
0.002571 |
0.00252 |
0.002408 |
0.002693 |
10 |
0.002496 |
0 |
|||
predict_proba |
skl |
1 |
685 |
10000 |
200 |
10 |
10 |
1 |
0.002613 |
0.00288 |
0.002638 |
0.00266 |
0.002664 |
0.002613 |
0.002809 |
10 |
0.00264 |
0 |
|||
predict |
skl |
1 |
1.015e+04 |
1 |
200 |
20 |
10 |
1 |
5.324e-05 |
0.0007014 |
5.412e-05 |
5.758e-05 |
0.0001209 |
5.324e-05 |
0.0005002 |
10 |
5.534e-05 |
0 |
|||
predict_proba |
skl |
1 |
1.015e+04 |
1 |
200 |
20 |
10 |
1 |
6.933e-05 |
9.326e-05 |
7.754e-05 |
8.364e-05 |
7.993e-05 |
6.933e-05 |
9.151e-05 |
10 |
7.918e-05 |
0 |
|||
predict |
skl |
1 |
1.015e+04 |
10 |
200 |
20 |
10 |
1 |
5.938e-05 |
7.862e-05 |
6.32e-05 |
6.76e-05 |
6.504e-05 |
5.938e-05 |
7.552e-05 |
10 |
6.337e-05 |
0 |
|||
predict_proba |
skl |
1 |
1.015e+04 |
10 |
200 |
20 |
10 |
1 |
7.332e-05 |
9.129e-05 |
8.027e-05 |
8.461e-05 |
8.212e-05 |
7.332e-05 |
9.116e-05 |
10 |
8.126e-05 |
0 |
|||
predict |
skl |
1 |
1.015e+04 |
100 |
200 |
20 |
10 |
1 |
8.515e-05 |
0.0001135 |
8.876e-05 |
9.388e-05 |
9.303e-05 |
8.515e-05 |
0.0001088 |
10 |
8.977e-05 |
0 |
|||
predict_proba |
skl |
1 |
1.015e+04 |
100 |
200 |
20 |
10 |
1 |
0.0001026 |
0.0001197 |
0.0001077 |
0.0001111 |
0.0001092 |
0.0001026 |
0.000118 |
10 |
0.0001084 |
0 |
|||
predict |
skl |
1 |
1.015e+04 |
1000 |
200 |
20 |
10 |
1 |
0.0003352 |
0.0005956 |
0.0003493 |
0.0003684 |
0.0003806 |
0.0003352 |
0.0005239 |
10 |
0.0003592 |
0 |
|||
predict_proba |
skl |
1 |
1.015e+04 |
1000 |
200 |
20 |
10 |
1 |
0.0003661 |
0.0005044 |
0.0003714 |
0.0003909 |
0.0003897 |
0.0003661 |
0.0004671 |
10 |
0.0003754 |
0 |
|||
predict |
skl |
1 |
1.015e+04 |
10000 |
200 |
20 |
10 |
1 |
0.003368 |
0.003638 |
0.003402 |
0.003469 |
0.003435 |
0.003368 |
0.003581 |
10 |
0.003403 |
0 |
|||
predict_proba |
skl |
1 |
1.015e+04 |
10000 |
200 |
20 |
10 |
1 |
0.003551 |
0.003911 |
0.003571 |
0.003692 |
0.003636 |
0.003551 |
0.00384 |
10 |
0.003587 |
0 |
Benchmark code#
bench_plot_onnxruntime_decision_tree.py
# coding: utf-8
"""
Benchmark of :epkg:`onnxruntime` on DecisionTree.
"""
# Authors: Xavier Dupré (benchmark)
# License: MIT
import matplotlib
matplotlib.use('Agg')
import os
from time import perf_counter as time
import numpy
import pandas
import matplotlib.pyplot as plt
import sklearn
from sklearn.tree import DecisionTreeClassifier
from sklearn.utils._testing import ignore_warnings
from sklearn.utils.extmath import softmax
from scipy.special import expit
from pymlbenchmark.context import machine_information
from pymlbenchmark.benchmark import BenchPerf
from pymlbenchmark.external import OnnxRuntimeBenchPerfTestBinaryClassification
from pymlbenchmark.plotting import plot_bench_results
model_name = "DecisitionTreeClassifier"
filename = os.path.splitext(os.path.split(__file__)[-1])[0]
@ignore_warnings(category=FutureWarning)
def run_bench(repeat=10, verbose=False):
pbefore = dict(dim=[1, 5, 10, 20, 50, 100, 200],
max_depth=[3, 10, 20])
pafter = dict(N=[1, 10, 100, 1000, 10000])
test = lambda dim=None, **opts: OnnxRuntimeBenchPerfTestBinaryClassification(
DecisionTreeClassifier, dim=dim, **opts)
bp = BenchPerf(pbefore, pafter, test)
with sklearn.config_context(assume_finite=True):
start = time()
results = list(bp.enumerate_run_benchs(repeat=repeat, verbose=verbose,
stop_if_error=False))
end = time()
results_df = pandas.DataFrame(results)
print("Total time = %0.3f sec\n" % (end - start))
return results_df
#########################
# Runs the benchmark
# ++++++++++++++++++
df = run_bench(verbose=True)
df.to_csv("%s.perf.csv" % filename, index=False)
print(df.head())
#########################
# Extract information about the machine used
# ++++++++++++++++++++++++++++++++++++++++++
pkgs = ['numpy', 'pandas', 'sklearn', 'skl2onnx',
'onnxruntime', 'onnx', 'mlprodict']
dfi = pandas.DataFrame(machine_information(pkgs))
dfi.to_csv("%s.time.csv" % filename, index=False)
print(dfi)
#############################
# Plot the results
# ++++++++++++++++
def label_fct(la):
la = la.replace("onxpython_compiled", "opy")
la = la.replace("onxpython", "opy")
la = la.replace("onxonnxruntime1", "ort")
la = la.replace("fit_intercept", "fi")
la = la.replace("True", "1")
la = la.replace("False", "0")
la = la.replace("max_depth", "mxd")
return la
plot_bench_results(df, row_cols='N', col_cols='method',
x_value='dim', hue_cols='max_depth',
title="%s\nBenchmark scikit-learn / onnxruntime" % model_name,
label_fct=label_fct)
plt.savefig("%s.png" % filename)
import sys
if "--quiet" not in sys.argv:
plt.show()