47,133 repositories indexed
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Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
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.
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
A collection of environments for autonomous driving and tactical decision-making tasks
TranslatedNon-autoregressive System 1 decision engine, designed for structured, typed decision-making scenarios. DeepOpen Multilingual, non-autoregressive System 1 decision engine.
ID3-based implementation of the ML Decision Tree algorithm
Artificial Intelligence framework for games based on libGDX or not. Features: Steering Behaviors, Formation Motion, Pathfinding, Behavior Trees and Finite State Machines
A clinical decision-evidence benchmark: pull the one fact an answer rests on, and see whether the assistant's action moves with the evidence. Built on HealthBench.
Ensembles of decision trees in go/golang.
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
Translated斑海豹 (Spotted Seal) — Phocinae-Largha-150M-v1: a 144.3M bilingual decision model. Tiny model. Big decisions.
Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models
Laya typed decisions on Linux x86_64 via ONNX Runtime
Maze Applied Reinforcement Learning Framework
TavernGym and TavernBench: a faithful, full-content Hearthstone Battlegrounds simulator with an RL interface, and a 960-task decision benchmark. Code and data for "Build, Don't Play".
Go Scoring API for PMML
Ruby Scoring API for PMML
Golang Dynamic Decision Tree
CatBoost a fast, scalable, high performance Gradient Boosting on Decision Trees library. Golang using Cgo for blazing fast inference CatBoost Model 🚀
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.