14 open-source projects similar to kei500/liblinear-ruby, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Liblinear Ruby alternative.
dlib is a C++ machine learning toolkit and data analysis framework. It provides a collection of algorithms and utilities for building predictive modeling applications and performing statistical analysis on large datasets within native C++ environments. The project functions as a binding library that wraps low-level C++ machine learning algorithms into high-level Python scripting interfaces. This allows for the integration of high-performance native implementations with Python for machine learning development. The framework covers the implementation of predictive models, the execution of mach
Linnaeus is a redis-backed naive Bayesian classification system. Please see the rdoc for more information. Ruby 1.9 is required.
This wrapper is based on C-code by David M. Blei. In a nutshell, it can be used to automatically cluster documents into topics. The number of topics are chosen beforehand and the topics found are usually fairly intuitive. Details of the implementation can be found in the paper by Blei, Ng, and…
ID3-based implementation of the ML Decision Tree algorithm
A Naive Bayes text classification implementation as an OmniCat classifier strategy.
This is the Ruby interface to LIBLINEAR (much more efficient than LIBSVM for text classification and other large linear classifications)