Classification Models Python Packages

treeig

Exact Integrated Gradients for tree ensembles, including XGBoost, LightGBM, Random Forests, and Gradient Boosting. Computes fast, exact feature attributions for tree models without numerical gradients, numerical integration, Monte Carlo sampling, or path approximations.

edef

Feature attribution for realized model fit (rather than predictions). EDEF provides exact additive decomposition of predictive performance for linear, PyTorch, JAX, and tree-based models, including standard errors, grouped inference, and exact TreeIG decompositions for tree-based models.

lazypredict-nightly

Lazy Predict Nightly enables rapid benchmarking of machine learning models with just a few lines of code. It helps identify the best-performing algorithms on your dataset without requiring hyperparameter tuning.

cobraclassifier

COBRA for Classification tasks on Imbalanced Data

intelelm

IntelELM: A Python Framework for Intelligent Metaheuristic-based Extreme Learning Machine

hyperbox-brain

A scikit-learn compatible hyperbox-based machine learning library in Python

metaperceptron

MetaPerceptron: A Standardized Framework For Metaheuristic-Driven Multi-layer Perceptron Optimization

pactus

Framework to evaluate Trajectory Classification Algorithms

embml

A tool to support using classification models in low-power microcontroller-based hardware

imbcobra

COBRA for Classification tasks on Imbalanced Data