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Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

A flexible and general-purpose ngrams library written in Ruby. Raingrams supports ngram sizes greater than 1, text/non-text grams, multiple parsing styles and open/closed vocabulary models.

  • ruby
  • ngrams

Minerva Story is an image viewer that is designed specifically to make it easy for non-expert users to interact with complex tissue images.

  • minerva
  • microscopy
  • ome
  • immunofluorescence

extensible, type-and-source-polymorphic, non-linear applicative parser combinator library for F# 3.0 and 4.0

  • f-sharp
  • parser
  • combinator
  • library