21 Apr '17, 3am

Useful resources for Machine Learning in Ruby #ruby #rails

Useful resources for Machine Learning in Ruby #ruby #rails

rb-libsvm - Support Vector Machines with Ruby. weka-jruby - JRuby bindings for Weka, different ML algorithms implemented through Weka. decisiontree - Decision Tree ID3 Algorithm in pure Ruby [post ] . rtimbl - Memory based learners from the Timbl framework. classifier-reborn - General classifier module to allow Bayesian and other types of classifications. lda-ruby - Ruby implementation of the LDA (Latent Dirichlet Allocation) for automatic Topic Modelling and Document Clustering. liblinear-ruby-swig - Ruby interface to LIBLINEAR (much more efficient than LIBSVM for text classification). linnaeus - Redis-backed Bayesian classifier. maxent_string_classifier - JRuby maximum entropy classifier for string data, based on the OpenNLP Maxent framework. naive_bayes - Simple Naive Bayes classifier. nbayes - Full-featured, Ruby implementation of Naive Bayes. omnicat - Generalized rac...

Full article: https://github.com/arbox/machine-learning-with-ruby

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