Popular GitHub Repositories for Categorical

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.

Modularized Implementation of Deep RL Algorithms in PyTorch

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

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

Mixed continous/categorical flow-matching model for de novo molecule generation.

A working implementation of the Categorical DQN (Distributional RL).

This repository contains a notebook demonstrating a practical implementation of the so-called Entity Embedding for Encoding Categorical Features for Training a Neural Network.

Discover relevant information about categorical data with entity embeddings using Neural Networks (powered by Keras)

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

Embed categorical variables via neural networks.

Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.

Bayesian Optimization for Categorical and Continuous Inputs

A library for the hyperparameter optimization of deep neural networks

[CIKM'21] Spatio-Temporal-Categorical Graph Neural Networks for Fine-Grained Multi-Incident Co-Prediction

ReLAx - Reinforcement Learning Applications Library

DILMA: Differentiable Language Model Adversarial Attacks on Categorical Sequence Classifiers

A Python framework for deploying recommendation models for form fields.

PyTorch autoencoder with additional embeddings layer for categorical data ?

Official implementation of "Weakly Supervised Intracranial Hemorrhage Segmentation using Head-Wise Gradient-Infused Self-Attention Maps from a Swin Transformer in Categorical Learning."