Notebooks Coverage

Report on last executions.

100% 2019-09-15

index	coverage	exe time	last execution	name	title	success	time	nb cells	nb runs	nb valid
0	100%	27.572	2019-09-15	explore/search_images_keras.ipynb	Search images with deep learning (keras)	True	28.559	49	49	49
1	100%	16.458	2019-09-15	explore/search_images_torch.ipynb	Search images with deep learning (torch)	True	17.335	31	31	31
2	100%	72.142	2019-09-15	sklearn/faster_polynomial_features.ipynb	Faster Polynomial Features	True	72.962	26	26	26
3	100%	4.799	2019-09-15	sklearn/logistic_regression_clustering.ipynb	LogisticRegression and Clustering	True	5.612	16	16	16
4	100%	11.054	2019-09-15	sklearn/piecewise_classification.ipynb	Piecewise classification with scikit-learn predictors	True	11.863	16	16	16
5	100%	3.969	2019-09-15	sklearn/piecewise_linear_regression.ipynb	Piecewise linear regression with scikit-learn predictors	True	4.759	18	18	18
6	100%	25.333	2019-09-15	sklearn/predictable_tsne.ipynb	Predictable t-SNE	True	26.628	16	16	16
7	100%	2.070	2019-09-15	sklearn/quantile_mlpregression.ipynb	Quantile MLPRegressor	True	3.094	6	6	6
8	100%	3.243	2019-09-15	sklearn/quantile_regression.ipynb	Quantile Regression	True	4.025	14	14	14
9	100%	6.066	2019-09-15	sklearn/regression_confidence_interval.ipynb	Regression with confidence interval	True	6.867	24	24	24
10	100%	11.226	2019-09-15	sklearn/sklearn_transformed_target.ipynb	Transformed Target	True	12.022	27	27	27
11	100%	1.368	2019-09-15	sklearn/traceable_ngrams_tfidf.ipynb	Traceable n-grams with tf-idf	True	5.310	10	10	10
12	100%	2.858	2019-09-15	sklearn/visualize_pipeline.ipynb	Visualize a scikit-learn pipeline	True	3.667	25	25	25
13	100%	58.568	2019-09-15	sklearn_c/piecewise_linear_regression_criterion.ipynb	Custom DecisionTreeRegressor adapted to a linear regression	True	59.375	32	32	32
14	100%	4.540	2019-09-15	tree/leave_neighbors.ipynb	Close leaves in a decision trees	True	5.393	15	15	15