| Name | mlinsights JSON |
| Version |
0.5.0
JSON |
| download |
| home_page | https://github.com/sdpython/mlinsights |
| Summary | Extends the list of supported operators in onnx reference implementation and onnxruntime, or implements faster versions in C++. |
| upload_time | 2023-11-05 12:20:27 |
| maintainer | |
| docs_url | None |
| author | Xavier Dupré |
| requires_python | >=3.9 |
| license | Copyright (c) 2017-2023, Xavier Dupré Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
onnx
cython
scikit-learn
machine-learning
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
.. image:: https://github.com/sdpython/mlinsights/blob/main/_doc/sphinxdoc/source/_static/project_ico.png?raw=true
:target: https://github.com/sdpython/mlinsights/
mlinsights: extensions to scikit-learn
======================================
.. image:: https://dev.azure.com/xavierdupre3/mlinsights/_apis/build/status%2Fsdpython.mlinsights%20(2)?branchName=main
:target: https://dev.azure.com/xavierdupre3/mlinsights/_build/latest?definitionId=16&branchName=main
.. image:: https://badge.fury.io/py/mlinsights.svg
:target: http://badge.fury.io/py/mlinsights
.. image:: https://img.shields.io/badge/license-MIT-blue.svg
:alt: MIT License
:target: http://opensource.org/licenses/MIT
.. image:: https://codecov.io/github/sdpython/mlinsights/coverage.svg?branch=main
:target: https://codecov.io/github/sdpython/mlinsights?branch=main
.. image:: http://img.shields.io/github/issues/sdpython/mlinsights.png
:alt: GitHub Issues
:target: https://github.com/sdpython/mlinsights/issues
.. image:: https://pepy.tech/badge/mlinsights/month
:target: https://pepy.tech/project/mlinsights/month
:alt: Downloads
.. image:: https://img.shields.io/github/forks/sdpython/mlinsights.svg
:target: https://github.com/sdpython/mlinsights/
:alt: Forks
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:target: https://github.com/sdpython/mlinsights/
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.. image:: https://img.shields.io/github/repo-size/sdpython/mlinsights
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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.
**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 <https://sdpython.github.io/doc/mlinsights/dev/>`_
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