scikit-learn-contrib/scikit-learn-contrib.github.io

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scikit-learn-contrib/scikit-learn-contrib.github.io

scikit-learn-contrib

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Project webpage

imbalanced-learn

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

sklearn-pandas

Pandas integration with sklearn

hdbscan

A high performance implementation of HDBSCAN clustering.

Jupyter Notebook

category_encoders

A library of sklearn compatible categorical variable encoders

lightning

Large-scale linear classification, regression and ranking in Python

boruta_py

Python implementations of the Boruta all-relevant feature selection method.

metric-learn

Metric learning algorithms in Python

MAPIE

A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.

Jupyter Notebook

skope-rules

machine learning with logical rules in Python

Jupyter Notebook

DESlib

A Python library for dynamic classifier and ensemble selection

py-earth

A Python implementation of Jerome Friedman's Multivariate Adaptive Regression Splines

scikit-learn-contrib

scikit-learn compatible projects

project-template

A template for scikit-learn extensions

forest-confidence-interval

Confidence intervals for scikit-learn forest algorithms

polylearn

A library for factorization machines and polynomial networks for classification and regression in Python.

stability-selection

scikit-learn compatible implementation of stability selection.

skglm

Fast and modular sklearn replacement for generalized linear models

scikit-learn-extra

scikit-learn contrib estimators

qolmat

A scikit-learn-compatible module for comparing imputation methods.

hiclass

A python library for hierarchical classification compatible with scikit-learn

scikit-dimension

A Python package for intrinsic dimension estimation

scikit-matter

A collection of scikit-learn compatible utilities that implement methods born out of the materials science and chemistry communities

skdag

A more flexible alternative to scikit-learn Pipelines

denmune-clustering-algorithm

DenMune a clustering algorithm that can find clusters of arbitrary size, shapes and densities in two-dimensions. Higher dimensions are first reduced to 2-D using the t-sne. The algorithm relies on a single parameter K (the number of nearest neighbors). The results show the superiority of DenMune. Enjoy the simplicty but the power of DenMune.

Jupyter Notebook

mimic

mimic calibration

sklearn-ann

Integration with (approximate) nearest neighbors libraries for scikit-learn + clustering based on with kNN-graphs.