ThumbsUp provides dead-simple voting capabilities to ActiveRecord models with karma calculation, a la stackoverflow.com.

Read more documentation at repository homepage.

A/B test analysis library for Ruby

Abstat is a simple library to help with analyzing the results of A/B test.

The Gem for Experimental Computer Science (GECS) is for managing the data resulting from experiments on software and IT systems. It realizes a data model that disambiguates the vocabulary of experimentation and measurement for a computer science audience. It also provides convenience functions to determine confidence intervals, analyze main effects and interactions, and export data in an R-compatible format for further analysis and visualization.

PETS suite includes three different tools. CohortAnalyzer performs the calculation of several statistics that gives an overview of a cohort of patients to analyse. Reg2Phen uses associations between pathological phenotypes and regions of the genome (these associations can be calculated from the cohort of patients if they include genotypic & phenotypic information using NetAnalyzer, another Ruby gem) to find, for a given genomic region, which pathological phenotypes have been associated with that region. The third tool, Phen2Reg, is a predictor that using the same associations as Reg2Phen, predicts which genomic regions can be the cause of a list of pathological phenotypes observed in a patient.

RubyNEAT -- Neural Evolution of Augmenting Topologies for Ruby. By way of an enhanced form of Genetic Algorithms -- the NEAT algorithm, populations of neural nets are evolved to handle pre-defined goals. RubyNEAT is the first implementation of the NEAT algorithm for Ruby, and it leverages Ruby's power to implement the NEAT algorithm in a way that would be difficult to do in other languages. The 'activation function' is largely standalone. Basically, activation is achieved by functional programming. Meaning, once your network is evolved, you can extract it as source code you can then utilize without the RubyNEAT engine. RubyNEAT can be used for nearly any Machine Learning task you can dream of, because it's also extensible and modular. See http://rubyneat.com for the details.

Runs a lower bound confidence score on scotchit's whisky review archive to generate buy recommendations.

Install gsl, statistics2 and provides a C extension to optimize the following methods * Vector#frecuencies * Vector#set_valid_data * Vector#check_type * Dataset#case_as_hash * Dataset#case_as_array * Bivariate::Tetrachoric

A small library for yes/no voting on ActiveRecord models.

Makes it super easy to calculate Wilson confidence intervals.