Repository Index

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.

• gbdt
• gbm
• machine-learning
• data-mining

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.

• machine-learning
• decision-trees
• gradient-boosting
• gbm

ThunderSVM: A Fast SVM Library on GPUs and CPUs

• classification
• regression
• one-class-learning
• cuda

A Modern C++ Data Sciences Toolkit

• nlp
• nlp-parsing
• search-engine
• inverted-index

This is the Ruby interface to LIBLINEAR (much more efficient than LIBSVM for text classification and other large linear classifications)

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

• svm
• regression
• classification
• machine-learning