CatBoost is a gradient boosting machine learning library used to train decision tree ensembles for regression, classification, and ranking tasks. It functions as a high-performance framework that provides a categorical data processor for transforming non-numeric features, a distributed trainer for large-scale datasets, and GPU acceleration to speed up model construction. The library distinguishes itself through native handling of categorical data and text features, removing the need for manual encoding. It includes a specialized model interpretability tool that leverages SHAP values and featu
pyclustering is a Python, C++ data mining library.
The main features of manifoldai/merf are: Clustering and Similarity, Decision Tree Models.
Open-source alternatives to manifoldai/merf include: bgu-cs-vil/deepdpm. catboost/catboost — CatBoost is a gradient boosting machine learning library used to train decision tree ensembles for regression,… cerlymarco/linear-tree. derrickburns/generalized-kmeans-clustering. dmlc/xgboost — XGBoost is a distributed machine learning library for implementing scalable gradient boosting decision trees used for… annoviko/pyclustering — pyclustering is a Python, C++ data mining library.