Modules

Summary

module

truncated documentation

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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

_piecewise_tree_regression_common.cpython-37m-x86_64-linux-gnu

module mlinsights.mlmodel._piecewise_tree_regression_common Implements a custom criterion to train a 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

direct_blas_lapack.cpython-37m-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

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-37m-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-37m-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-37m-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

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_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