__init__ |
module mlinsights Module mlinsights. Look for insights for machine learned models. source on GitHub |
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module mlinsights.helpers Shortcuts to helpers. source on GitHub |
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module mlinsights.metrics Shortcuts to metrics. source on GitHub |
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module mlinsights.mlbatch Shortcuts to mlbatch. source on GitHub |
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module mlinsights.mlmodel Shortcuts to mlmodel. source on GitHub |
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module mlinsights.mltree Shortcuts to mltree. source on GitHub |
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module mlinsights.plotting Shortcuts to plotting. source on GitHub |
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module mlinsights.search_rank Shortcuts to search_rank. source on GitHub |
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module mlinsights.sklapi Shortcuts for mltricks. source on GitHub |
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module mlinsights.timeseries Shortcut to timeseries. source on GitHub |
_extended_features_polynomial |
module mlinsights.mlmodel._extended_features_polynomial Implements new features such as polynomial features. source on GitHub |
_kmeans_022 |
module mlinsights.mlmodel._kmeans_022 Implements k-means with norms L1 and L2. source on GitHub |
_kmeans_constraint_ |
module mlinsights.mlmodel._kmeans_constraint_ Implémente la classe ConstraintKMeans. source on GitHub |
_piecewise_tree_regression_common.cpython-39-x86_64-linux-gnu |
module mlinsights.mlmodel._piecewise_tree_regression_common Implements a custom criterion to train a decision tree. source on GitHub |
_tree_digitize.cpython-39-x86_64-linux-gnu |
module mlinsights.mltree._tree_digitize Access to the C API of scikit-learn (decision tree) source on GitHub |
agg |
module mlinsights.timeseries.agg Data aggregation for timeseries. source on GitHub |
anmf_predictor |
module mlinsights.mlmodel.anmf_predictor Featurizers for machine learned models. source on GitHub |
ar |
module mlinsights.timeseries.ar Auto-regressor for timeseries. source on GitHub |
base |
module mlinsights.timeseries.base Base class for timeseries. source on GitHub |
cache_model |
module mlinsights.mlbatch.cache_model Caches to cache training. source on GitHub |
categories_to_integers |
module mlinsights.mlmodel.categories_to_integers Implements a transformation which can be put in a pipeline to transform categories in integers. source on GitHub |
classification_kmeans |
module mlinsights.mlmodel.classification_kmeans Combines a k-means followed by a predictor. source on GitHub |
correlations |
module mlinsights.metrics.correlations Correlations. source on GitHub |
datasets |
module mlinsights.timeseries.datasets Datasets for timeseries. source on GitHub |
decision_tree_logreg |
module mlinsights.mlmodel.decision_tree_logreg Builds a tree of logistic regressions. source on GitHub |
direct_blas_lapack.cpython-39-x86_64-linux-gnu |
module mlinsights.mlmodel.direct_blas_lapack Direct calls to libraries BLAS and LAPACK. source on GitHub |
dummies |
module mlinsights.timeseries.dummies Dummy auto-regressor which takes past values as predictions. source on GitHub |
extended_features |
module mlinsights.mlmodel.extended_features Implements new features such as polynomial features. source on GitHub |
gallery |
module mlinsights.plotting.gallery Featurizers for machine learned models. source on GitHub |
interval_regressor |
module mlinsights.mlmodel.interval_regressor Implements a piecewise linear regression. source on GitHub |
kmeans_constraint |
module mlinsights.mlmodel.kmeans_constraint Implémente la classe ConstraintKMeans. source on GitHub |
kmeans_l1 |
module mlinsights.mlmodel.kmeans_l1 Implements k-means with norms L1 and L2. source on GitHub |
metrics |
module mlinsights.timeseries.metrics Timeseries metrics. source on GitHub |
ml_featurizer |
module mlinsights.mlmodel.ml_featurizer Featurizers for machine learned models. source on GitHub |
parameters |
module mlinsights.helpers.parameters Functions about parameters. source on GitHub |
patterns |
module mlinsights.timeseries.patterns Find patterns in timeseries. source on GitHub |
piecewise_estimator |
module mlinsights.mlmodel.piecewise_estimator Implements a piecewise linear regression. source on GitHub |
piecewise_tree_regression |
module mlinsights.mlmodel.piecewise_tree_regression Implements a kind of piecewise linear regression by modifying the criterion used by the algorithm which builds a decision tree. source on GitHub |
piecewise_tree_regression_criterion.cpython-39-x86_64-linux-gnu |
module mlinsights.mlmodel.piecewise_tree_regression_criterion Implements a base class for a custom criterion to train a decision tree. source on GitHub |
piecewise_tree_regression_criterion_fast.cpython-39-x86_64-linux-gnu |
module mlinsights.mlmodel.piecewise_tree_regression_criterion_fast Implements a custom criterion to train a decision tree. source on GitHub |
piecewise_tree_regression_criterion_linear.cpython-39-x86_64-linux-gnu |
module mlinsights.mlmodel.piecewise_tree_regression_criterion_linear Implements a custom criterion to train a decision tree. source on GitHub |
pipeline |
module mlinsights.helpers.pipeline Dig into pipelines. source on GitHub |
pipeline_cache |
module mlinsights.mlbatch.pipeline_cache Caches training. source on GitHub |
plotting |
module mlinsights.timeseries.plotting Timeseries plots. source on GitHub |
predictable_tsne |
module mlinsights.mlmodel.predictable_tsne Implements a predicatable t-SNE. source on GitHub |
preprocessing |
module mlinsights.timeseries.preprocessing Timeseries preprocessing. source on GitHub |
quantile_mlpregressor |
module mlinsights.mlmodel.quantile_mlpregressor Implements a quantile non-linear regression. source on GitHub |
quantile_regression |
module mlinsights.mlmodel.quantile_regression Implements a quantile linear regression. source on GitHub |
scoring_metrics |
module mlinsights.metrics.scoring_metrics Metrics to compare machine learning. source on GitHub |
search_engine_predictions |
module mlinsights.search_rank.search_engine_predictions Implements a way to get close examples based on the output of a machine learned model. source on GitHub |
search_engine_predictions_images |
module mlinsights.search_rank.search_engine_predictions_images Implements a way to get close examples based on the output of a machine learned model. source on GitHub |
search_engine_vectors |
module mlinsights.search_rank.search_engine_vectors Implements a way to get close examples based on the output of a machine learned model. source on GitHub |
sklearn_base |
module mlinsights.sklapi.sklearn_base Implements a learner or a transform which follows the same API as every scikit-learn transform. source on GitHub |
sklearn_base_classifier |
module mlinsights.sklapi.sklearn_base_classifier Implements class SkBaseClassifier. source on GitHub |
sklearn_base_learner |
module mlinsights.sklapi.sklearn_base_learner Implements a learner which follows the same API as every scikit-learn learner. source on GitHub |
sklearn_base_regressor |
module mlinsights.sklapi.sklearn_base_regressor Implements SkBaseRegressor. source on GitHub |
sklearn_base_transform |
module mlinsights.sklapi.sklearn_base_transform Implements a transform which follows the smae API as every scikit-learn transform. source on GitHub |
sklearn_base_transform_learner |
module mlinsights.sklapi.sklearn_base_transform_learner Implements a transform which converts a learner into a transform. source on GitHub |
sklearn_base_transform_stacking |
module mlinsights.sklapi.sklearn_base_transform_stacking Implémente un transform qui suit la même API que tout scikit-learn transform. source on GitHub |
sklearn_parameters |
module mlinsights.sklapi.sklearn_parameters Defines class SkLearnParameters. source on GitHub |
sklearn_testing |
module mlinsights.mlmodel.sklearn_testing Helpers to test a model which follows scikit-learn API. source on GitHub |
sklearn_text |
module mlinsights.mlmodel.sklearn_text Overloads TfidfVectorizer and CountVectorizer. source on GitHub |
sklearn_transform_inv |
module mlinsights.mlmodel.sklearn_transform_inv Implements a base class which defines a pair of transforms applied around a predictor to modify the target as well. source on GitHub |
sklearn_transform_inv_fct |
module mlinsights.mlmodel.sklearn_transform_inv_fct Implements a transform which modifies the target and applies the reverse transformation on the target. source on GitHub |
target_predictors |
module mlinsights.mlmodel.target_predictors Implements a slightly different version of the sklearn.compose.TransformedTargetRegressor. source on GitHub |
transfer_transformer |
module mlinsights.mlmodel.transfer_transformer Implements a transformer which wraps a predictor to do transfer learning. source on GitHub |
tree_digitize |
module mlinsights.mltree.tree_digitize Helpers to investigate a tree structure. .. versionadded:: 0.4 source on GitHub |
tree_structure |
module mlinsights.mltree.tree_structure Helpers to investigate a tree structure. source on GitHub |
utils |
module mlinsights.timeseries.utils Timeseries data manipulations. source on GitHub |
visualize |
module mlinsights.plotting.visualize Helpers to visualize a pipeline. source on GitHub |