Modules

Summary

module truncated documentation
__init__ module mlinsights Module mlinsights. Look for insights for machine learned models. source on GitHub
__init__ module mlinsights.featurizers Shortcuts to featurizers. source on GitHub
__init__ module mlinsights.metrics Shortcuts to metrics. source on GitHub
__init__ module mlinsights.mlmodel Shortcuts to mlmodel. source on GitHub
__init__ module mlinsights.plotting Shortcuts to plotting. source on GitHub
__init__ module mlinsights.search_rank Shortcuts to search_rank. source on GitHub
__init__ module mlinsights.sklapi Shortcuts for mltricks. 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 Implements a quantile linear regression. source on GitHub
correlations module mlinsights.metrics.correlations Correlations. source on GitHub
gallery module mlinsights.plotting.gallery Featurizers for machine learned models. source on GitHub
ml_featurizer module mlinsights.featurizers.ml_featurizer Featurizers for machine learned models. source on GitHub
parameters module mlinsights.helpers.parameters Functions about parameters. source on GitHub
quantile_mlpregressor module mlinsights.mlmodel.quantile_mlpregressor Implements a quantile linear regression. source on GitHub
quantile_regression module mlinsights.mlmodel.quantile_regression Implements a quantile linear regression. 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