Extends the list of supported operators in onnx reference implementation and onnxruntime, or implements faster versions in C++.

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  • License: MIT License (Copyright (c) 2017-2024, Xavier Dupré Permission is hereby granted, free of charge, to any person ...)
  • Author: Xavier Dupré
  • Tags onnx, cython, scikit-learn, machine-learning
  • Requires: Python >=3.9
  • Provides-Extra: dev
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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

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