Metadata-Version: 2.1
Name: mlinsights
Version: 0.3.539
Summary: Extends scikit-learn with a couple of new models, transformers, metrics, plotting.
Home-page: http://www.xavierdupre.fr/app/mlinsights/helpsphinx/index.html
Author: Xavier Dupré
Author-email: xavier.dupre@gmail.com
License: MIT
Download-URL: https://github.com/sdpython/mlinsights/
Keywords: mlinsights,Xavier Dupré
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Education
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 5 - Production/Stable
Requires-Dist: cython
Requires-Dist: scikit-learn (>=0.22.1)
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: pandas-streaming
Requires-Dist: numpy (>=1.16)


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.. _l-README:

mlinsights - extensions to scikit-learn
=======================================

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    :alt: Notebook Coverage

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    :alt: size

*mlinsights* extends *scikit-learn* with a couple of new models,
transformers, metrics, plotting. It provides new trainers such as
*QuantileLinearRegression* which trains a linear regression with *L1* norm
non-linear correlation based on decision trees, or
*QuantileMLPRegressor* a modification of scikit-learn's MLPRegressor
which trains a multi-layer perceptron with *L1* norm.
It also explores *PredictableTSNE* which trains a supervized
model to replicate *t-SNE* results or a *PiecewiseRegression*
which partitions the data before fitting a model on each bucket.

* `GitHub/mlinsights <https://github.com/sdpython/mlinsights/>`_
* `documentation <http://www.xavierdupre.fr/app/mlinsights/helpsphinx/index.html>`_
* `Blog <http://www.xavierdupre.fr/app/mlinsights/helpsphinx/blog/main_0000.html#ap-main-0>`_

Function ``pipeline2dot`` converts a pipeline into a graph:

::

    from mlinsights.plotting import pipeline2dot
    dot = pipeline2dot(clf, df)

.. image:: https://github.com/sdpython/mlinsights/raw/master/_doc/pipeline.png

.. _l-HISTORY:

=======
History
=======

current - 2021-01-03 - 0.00Mb
=============================

* `89`: Install fails: ModuleNotFoundError: No module named 'sklearn' (2021-01-03)
* `92`: QuantileMLPRegressor does not work with scikit-learn 0.24 (2021-01-01)
* `91`: Fixes regression criterion for scikit-learn 0.24 (2021-01-01)
* `90`: Fixes PipelineCache for scikit-learn 0.24 (2021-01-01)

0.2.508 - 2020-09-02 - 0.43Mb
=============================

* `88`: Change for scikit-learn 0.24 (2020-09-02)
* `87`: Set up CI with Azure Pipelines (2020-09-02)
* `86`: Update CI, use python 3.8 (2020-09-02)
* `71`: update kmeans l1 to the latest kmeans (signatures changed) (2020-08-31)
* `84`: style (2020-08-30)

0.2.491 - 2020-08-06 - 0.83Mb
=============================

* `83`: Upgrade version (2020-08-06)
* `82`: Fixes #81, skl 0.22, 0.23 together (2020-08-06)
* `81`: Make mlinsights work with scikit-learn 0.22 and 0.23 (2020-08-06)
* `79`: pipeline2dot fails with 'passthrough' (2020-07-16)

0.2.463 - 2020-06-29 - 0.83Mb
=============================

* `78`: Removes strong dependency on pyquickhelper (2020-06-29)

0.2.450 - 2020-06-08 - 0.83Mb
=============================

* `77`: Add parameter trainable to TransferTransformer (2020-06-07)

0.2.447 - 2020-06-03 - 0.83Mb
=============================

* `76`: ConstraintKMeans does not produce convex clusters. (2020-06-03)
* `75`: Moves kmeans with constraint from papierstat. (2020-05-27)
* `74`: Fix PipelineCache after as scikti-learn 0.23 changed the way parameters is handle in pipelines (2020-05-15)
* `73`: ClassifierKMeans.__repr__ fails with scikit-learn 0.23 (2020-05-14)
* `69`: Optimizes k-means with norm L1 (2020-01-13)

0.2.360 - 2019-09-15 - 0.68Mb
=============================

* `66`: Fix visualisation graph: does not work when column index is an integer in ColumnTransformer (2019-09-15)
* `59`: Add GaussianProcesses to the notebook about confidence interval and regression (2019-09-15)
* `65`: Implements a TargetTransformClassifier similar to TargetTransformRegressor (2019-08-24)
* `64`: Implements a different version of TargetTransformRegressor which includes predefined functions (2019-08-24)
* `63`: Add a transform which transform the target and applies the inverse function of the prediction before scoring (2019-08-24)
* `49`: fix menu in documentation (2019-08-24)

0.2.312 - 2019-07-13 - 0.66Mb
=============================

* `61`: Fix bug in pipeline2dot when keyword "passthrough is used" (2019-07-11)
* `60`: Fix visualisation of pipeline which contains string "passthrough" (2019-07-09)
* `58`: Explores a way to compute recommandations without training (2019-06-05)

0.2.288 - 2019-05-28 - 0.66Mb
=============================

* `56`: Fixes #55, explore caching for scikit-learn pipeline (2019-05-22)
* `55`: Explore caching for gridsearchCV (2019-05-22)
* `53`: implements a function to extract intermediate model outputs within a pipeline (2019-05-07)
* `51`: Implements a tfidfvectorizer which keeps more information about n-grams (2019-04-26)
* `46`: implements a way to determine close leaves in a decision tree (2019-04-01)
* `44`: implements a model which produces confidence intervals based on bootstrapping (2019-03-29)
* `40`: implements a custom criterion for a decision tree optimizing for a linear regression (2019-03-28)
* `39`: implements a custom criterion for decision tree (2019-03-26)
* `41`: implements a direct call to a lapack function from cython (2019-03-25)
* `38`: better implementation of a regression criterion (2019-03-25)

0.1.199 - 2019-03-05 - 0.05Mb
=============================

* `37`: implements interaction_only for polynomial features (2019-02-26)
* `36`: add parameter include_bias to extended features (2019-02-25)
* `34`: rename PiecewiseLinearRegression into PiecewiseRegression (2019-02-23)
* `33`: implement the piecewise classifier (2019-02-23)
* `31`: uses joblib for piecewise linear regression (2019-02-23)
* `30`: explore transpose matrix before computing the polynomial features (2019-02-17)
* `29`: explore different implementation of polynomialfeatures (2019-02-15)
* `28`: implement PiecewiseLinearRegression (2019-02-10)
* `27`: implement TransferTransformer (2019-02-04)
* `26`: add function to convert a scikit-learn pipeline into a graph (2019-02-01)
* `25`: implements kind of trainable t-SNE (2019-01-31)
* `6`: use keras and pytorch (2019-01-03)
* `22`: modifies plot gallery to impose coordinates (2018-11-10)
* `20`: implements a QuantileMLPRegressor (quantile regression with MLP) (2018-10-22)
* `19`: fix issues introduced with changes in keras 2.2.4 (2018-10-06)
* `18`: remove warning from scikit-learn about cloning (2018-09-16)
* `16`: move CI to python 3.7 (2018-08-21)
* `17`: replace as_matrix by values (pandas deprecated warning) (2018-07-29)
* `14`: add transform to convert a learner into a transform (sometimes called a  featurizer) (2018-06-19)
* `13`: add transform to do model stacking (2018-06-19)
* `8`: move items from papierstat (2018-06-19)
* `12`: fix bug in quantile regression: wrong weight for linear regression (2018-06-16)
* `11`: specifying quantile (2018-06-16)
* `4`: add function to compute non linear correlations (2018-06-16)
* `10`: implements combination between logistic regression and k-means (2018-05-27)
* `9`: move items from ensae_teaching_cs (2018-05-08)
* `7`: add quantile regression (2018-05-07)
* `5`: replace flake8 by code style (2018-04-14)
* `1`: change background for cells in notebooks converted into rst then in html, highlight-ipython3 (2018-01-05)
* `2`: save features and metadatas for the search engine and retrieves them (2017-12-03)


