LIBLINEAR v2.50 compiled to WebAssembly -- linear classification and regression in browsers and Node.js
Runtime core for wlearn: matrix helpers, bundle format, registry, pipeline
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AutoML engine for wlearn: search space sampling, random search, successive halving, ensemble construction
Ensemble methods for wlearn: voting, stacking, Caruana selection
Convenience barrel: re-exports all wlearn model classes, automl, ensemble, pipeline, and core utilities
Rust bindings for the liblinear C++ library
Rust bindings for the liblinear C++ library
FFI-free Rust implementation of LIBSVM-compatible SVM training and prediction
Lightweight, fast LinearSVC-style crate with Pegasos/DCD solvers, CSR input, OvR/OvO strategies, and optional Platt calibration.
Ruby wrapper of LIBLINEAR using SWIG
Numo::Liblinear is a Ruby gem binding to the LIBLINEAR library. LIBLINEAR is one of the famous libraries for large-scale regularized linear classification and regression. Numo::Liblinear makes to use the LIBLINEAR functions with dataset represented by Numo::NArray.
Ruby wrapper of LIBLINEAR using SWIG
Ruby wrapper of LIBLINEAR using SWIG
Ruby wrapper for LIBLINEAR, a library for large linear classification
Vector embedding of strings, booleans, numerics, and arrays into LIBSVM / LIBLINEAR format.
Rumale::SVM provides support vector machine algorithms using LIBSVM and LIBLINEAR with Rumale interface.
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