Categorical Features Python Packages

catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

catboost-dev

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

kts

Interactive ML Toolset

chefboost

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

henosis

A Python framework for deploying recommendation models for form fields.

category

Category transformation

catclass

MSC Project - Artifical Categorical Datasets

target-statistic-encoding

A lightweight library for encoding categorical features in your dataset with robust k-fold target statistics in training with credibility filtering, and custom statistics.

catboost-no-sse4

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

dsawl

A set of tools for machine learning (for the current day, there are active learning utilities and implementations of some stacking-based techniques).

cfed

A python package to compute pairwise Euclidean distances on datasets with categorical features in little time