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haifengl/smile

Statistical Machine Intelligence & Learning Engine

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

5083 1007 47

transcendent-ai-labs/dynaml

Scala Library/REPL for Machine Learning Research

Scala (JVM): 2.11

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

161 45 4

zenecture/neuroflow

Artificial Neural Networks for Scala

Scala (JVM): 2.11 2.12

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

95 6 2

citrineinformatics/lolo

A random forest

Scala (JVM): 2.12 2.13

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

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

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

14 2 3

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haifengl/smile

transcendent-ai-labs/dynaml

zenecture/neuroflow

citrineinformatics/lolo

liquidsvm/liquidsvm