https://github.com/sdpython/mlinsights

Extends scikit-learn with new models, transformers, metrics, plotting.
https://github.com/sdpython/mlinsights

algorithms machine-learning python3 scikit-learn

Last synced: about 8 hours ago
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Extends scikit-learn with new models, transformers, metrics, plotting.

• Host: GitHub
• URL: https://github.com/sdpython/mlinsights
• Owner: sdpython
• License: mit
• Created: 2017-11-18T19:48:01.000Z (almost 7 years ago)
• Default Branch: main
• Last Pushed: 2024-09-14T08:50:34.000Z (19 days ago)
• Last Synced: 2024-09-14T19:46:52.736Z (19 days ago)
• Topics: algorithms, machine-learning, python3, scikit-learn
• Language: Python
• Homepage: http://www.xavierdupre.fr/app/mlinsights/helpsphinx/index.html
• Size: 31.6 MB
• Stars: 69
• Watchers: 7
• Forks: 13
• Open Issues: 15
• Metadata Files:
  • Readme: README.rst
  • Changelog: CHANGELOGS.rst
  • License: LICENSE.txt
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        

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mlinsights: extensions to scikit-learn

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*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.

**PiecewiseTreeRegressor** trains a piecewise regressor using

a linear regression on each piece. **IntervalRegressor** produces

confidence interval by using bootstrapping. **ApproximateNMFPredictor**

approximates a NMF to produce prediction without retraining.

`mlinsights documentation `_