Skip to main content

Extends scikit-learn with a couple of new models, transformers, metrics, plotting.

Project description

Build status Build Status Windows https://circleci.com/gh/sdpython/mlinsights/tree/master.svg?style=svg https://dev.azure.com/xavierdupre3/mlinsights/_apis/build/status/sdpython.mlinsights https://badge.fury.io/py/mlinsights.svg MIT License Requirements Status https://codecov.io/github/sdpython/mlinsights/coverage.svg?branch=master GitHub Issues Notebook Coverage

mlinsights - extensions to scikit-learn

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.

History

current - 2019-05-23 - 0.00Mb

  • 55: Explore caching for gridsearchCV (2019-05-22)

  • 56: Fixes #55, explore caching for scikit-learn pipeline (2019-05-22)

0.2.269 - 2019-05-20 - 0.41Mb

  • 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)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mlinsights-0.2.288.tar.gz (693.7 kB view details)

Uploaded Source

File details

Details for the file mlinsights-0.2.288.tar.gz.

File metadata

  • Download URL: mlinsights-0.2.288.tar.gz
  • Upload date:
  • Size: 693.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: Python-urllib/3.7

File hashes

Hashes for mlinsights-0.2.288.tar.gz
Algorithm Hash digest
SHA256 91dc222513ea7f1dd75e6fa5ea50d007619fe5211854db5c0a6bcdae45673645
MD5 d24f9a540e717cf229fc3bb1c56c2473
BLAKE2b-256 a54ae663e8c131f775e77f6164a13d676d450031085bdc4e621e4572d5fc0c62

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page