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haifengl/smile

Statistical Machine Intelligence & Learning Engine

genetic-algorithm visualization interpolation statistics wavelet data-science dataframe deep-learning classification multidimensional-scaling clustering regression nearest-neighbor-search computer-algebra-system machine-learning graph linear-algebra nlp manifold-learning

5083 1007 47

transcendent-ai-labs/dynaml

Scala Library/REPL for Machine Learning Research

Scala (JVM): 2.11

machine-learning-algorithms kernel-methods tensorflow machine-learning-api classification regression machine-learning gaussian-processes repl scala committee-models scala-library

161 45 4

zenecture/neuroflow

Artificial Neural Networks for Scala

Scala (JVM): 2.11 2.12

artificial-neural-networks data-artistry classification clustering regression scala pattern-recognition data-science

95 6 2

citrineinformatics/lolo

A random forest

Scala (JVM): 2.12 2.13

machine-learning-algorithms random-forest jackknife-variance-estimates classification uncertainty regression

24 13 10

liquidsvm/liquidsvm

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.

Scala (JVM): 2.11

c-plus-plus python matlab r-package rstats quantile-regression svm apache-spark classification regression machine-learning ml expectile-regression octave r

14 2 3

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haifengl/smile

transcendent-ai-labs/dynaml

zenecture/neuroflow

citrineinformatics/lolo

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