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.

unifiedig

Provides a unified approach to Integrated Gradients: a common API for many models, include tree-based models; and common baseline semantics with prediction-neutral baseline distributions as the default.

pactus

Framework to evaluate Trajectory Classification Algorithms

intelelm

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

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.

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

cobraclassifier

COBRA for Classification tasks on Imbalanced Data

embml

A tool to support using classification models in low-power and microcontroller-based embedded systems.

imbcobra

COBRA for Classification tasks on Imbalanced Data