Properties

Summary

property

class parent

truncated documentation

Keys

SkLearnParameters

Returns parameter names.

_estimator_type

PipelineCache

_final_estimator

PipelineCache

_pairwise

PipelineCache

classes_

PipelineCache

classes_

TransformedTargetClassifier2

Returns the classes.

degree

TimeSeriesDifference

Returns the degree.

feature_importances_

PiecewiseTreeRegressor

Return the feature importances. The importance of a feature is computed as the (normalized) total reduction …

idf_

TraceableTfidfVectorizer

inverse_transform

PipelineCache

Apply inverse transformations in reverse order All estimators in the pipeline must support inverse_transform. …

n_estimators_

IntervalRegressor

Returns the number of estimators = the number of buckets the data was split in.

n_estimators_

PiecewiseClassifier

Returns the number of estimators = the number of buckets the data was split in.

n_estimators_

PiecewiseEstimator

Returns the number of estimators = the number of buckets the data was split in.

n_estimators_

PiecewiseRegressor

Returns the number of estimators = the number of buckets the data was split in.

named_steps

PipelineCache

norm

TraceableTfidfVectorizer

partial_fit

CustomizedMultilayerPerceptron

Update the model with a single iteration over the given data. Parameters ———- X : {array-like, …

partial_fit

QuantileMLPRegressor

Update the model with a single iteration over the given data. Parameters ———- X : {array-like, …

smooth_idf

TraceableTfidfVectorizer

sublinear_tf

TraceableTfidfVectorizer

transform

PipelineCache

Apply transforms, and transform with the final estimator This also works where final estimator is None: all …

use_idf

TraceableTfidfVectorizer