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imbalanced-learn
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learningsklearn-pandas
Pandas integration with sklearnhdbscan
A high performance implementation of HDBSCAN clustering.category_encoders
A library of sklearn compatible categorical variable encoderslightning
Large-scale linear classification, regression and ranking in Pythonboruta_py
Python implementations of the Boruta all-relevant feature selection method.metric-learn
Metric learning algorithms in PythonMAPIE
A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.skope-rules
machine learning with logical rules in PythonDESlib
A Python library for dynamic classifier and ensemble selectionpy-earth
A Python implementation of Jerome Friedman's Multivariate Adaptive Regression Splinesscikit-learn-contrib
scikit-learn compatible projectsproject-template
A template for scikit-learn extensionsforest-confidence-interval
Confidence intervals for scikit-learn forest algorithmspolylearn
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 modelsscikit-learn-extra
scikit-learn contrib estimatorsqolmat
A scikit-learn-compatible module for comparing imputation methods.hiclass
A python library for hierarchical classification compatible with scikit-learnscikit-dimension
A Python package for intrinsic dimension estimationskdag
A more flexible alternative to scikit-learn Pipelinesdenmune-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.mimic
mimic calibrationsklearn-ann
Integration with (approximate) nearest neighbors libraries for scikit-learn + clustering based on with kNN-graphs.scikit-learn-contrib.github.io
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