Displaying 1 to 18 from 18 results

decisiontree - ID3-based implementation of the ML Decision Tree algorithm

  •    Ruby

A Ruby library which implements ID3 (information gain) algorithm for decision tree learning. Currently, continuous and discrete datasets can be learned.

machine-learning-with-ruby - Curated list: Resources for machine learning in Ruby.

  •    Ruby

Machine Learning is a field of Computational Science - often nested under AI research - with many practical applications due to the ability of resulting algorithms to systematically implement a specific solution without explicit programmer's instructions. Obviously many algorithms need a definition of features to look at or a biggish training set of data to derive the solution from. This curated list comprises awesome libraries, data sources, tutorials and presentations about Machine Learning utilizing the Ruby programming language.

nlp-with-ruby - Practical Natural Language Processing done in Ruby.

  •    Ruby

This curated list comprises awesome resources, libraries, information sources about computational processing of texts in human languages with the Ruby programming language. That field is often referred to as NLP, Computational Linguistics, HLT (Human Language Technology) and can be brought in conjunction with Artificial Intelligence, Machine Learning, Information Retrieval, Text Mining, Knowledge Extraction and other related disciplines. This list comes from our day to day work on Language Models and NLP Tools. Read why this list is awesome. Our FAQ describes the important decisions and useful answers you may be interested in.

pycall.rb - Calling Python functions from the Ruby language

  •    C

This library provides the features to directly call and partially interoperate with Python from the Ruby language. You can import arbitrary Python modules into Ruby modules, call Python functions with automatic type conversion from Ruby to Python. Type conversions from Ruby to Python are automatically performed for numeric, boolean, string, arrays, and hashes.

classifier-reborn - A general classifier module to allow Bayesian and other types of classifications

  •    Ruby

Classifier Reborn is a general classifier module to allow Bayesian and other types of classifications. It is a fork of cardmagic/classifier under more active development. Currently, it has Bayesian Classifier and Latent Semantic Indexer (LSI) implemented. Here is a quick illustration of the Bayesian classifier.

rb-libsvm - Ruby language bindings for LIBSVM

  •    C++

This package provides a Ruby bindings to the LIBSVM library. SVM is a machine learning and classification algorithm, and LIBSVM is a popular free implementation of it, written by Chih-Chung Chang and Chih-Jen Lin, of National Taiwan University, Taipei. See the book "Programming Collective Intelligence," among others, for a usage example. There is a JRuby implementation of this gem named jrb-libsvm by Andreas Eger.

scoruby - Ruby Scoring API for PMML

  •    Ruby

Ruby scoring API for Predictive Model Markup Language (PMML).Currently supports Decision Tree, Random Forest Naive Bayes and Gradient Boosted Models.

kmeans-clusterer - k-means clustering in Ruby

  •    Ruby

k-means clustering in Ruby. Uses NArray under the hood for fast calculations. Jump to the examples directory to see this in action.

mnist-ruby-test - Handwritten digit OCR in Ruby

  •    Ruby

Testing classification of MNIST digits in Ruby. Includes a Sinatra app that uses a trained ruby-fann neural network to predict digits drawn on a element. The neural network was trained on all 60,000 training examples with 1 hidden layer of 300 neurons, and successfully classified ~93% of the test set.

neural-net-ruby - A neural network, written in Ruby

  •    Ruby

A feedforward neural network with resilient backpropagation (Rprop). It's ~250 loc, 100% Ruby, with no external dependencies. This implementation trains significantly faster than ai4r's backpropagation neural network, mainly because the Rprop training algorithm implemented here is much faster than the non-batch backpropagation algorithm used in ai4r.

pca - Principal component analysis (PCA) in Ruby

  •    Ruby

Principal component analysis in Ruby. Uses GSL for calculations. PCA can be used to map data to a lower dimensional space while minimizing information loss. It's useful for data visualization, where you're limited to 2-D and 3-D plots.


  •    Ruby

This example will show how to implement a simple neural network for classification in Ruby using ruby-fann. For more information about this network see the blog post Implementing Simple Classification using a Neural Network in Ruby.

linear-regression - Linear regression implemented in Ruby.

  •    Ruby

An implementation of a linear regression machine learning algorithm implemented in Ruby. More details about this example implementation can be found in this blog post.


  •    Ruby

This example will show how we can teach an AI to play a simple game using the Q-learning reinforcement learning algorithm. This is implemented in pure Ruby without any external dependencies.

DNE - A set of neuroevolution experiments with/towards deep networks

  •    Ruby

This project collects a set of neuroevolution experiments with/towards deep networks for reinforcement learning using an unsupervised learning feature exctactor. First make sure the OpenAI Gym is pip-installed on python3, instructions here. You will also need the GVGAI_GYM to access GVGAI environments.


  •    C++

Liblinear-Ruby is Ruby interface of LIBLINEAR using SWIG. Now, this interface is supporting LIBLINEAR 2.11. This sample code execute classification with L2-regularized logistic regression.

weka-jruby - Machine Learning & Data Mining with JRuby

  •    Ruby

Machine Learning & Data Mining with JRuby based on the Weka Java library. The weka gem tries to carry over the namespaces defined in Weka and enhances some interfaces in order to allow a more Ruby-ish programming style when using the Weka library.

ruby-interoperability - Ruby Mixture with other Programming Languages


Ruby Interoperability by Andrei Beliankou and Contributors. To the extent possible under law, the person who associated CC0 with Ruby Interoperability has waived all copyright and related or neighboring rights to Ruby Interoperability.