Project details for YCML

Logo YCML 0.2.2

by yconst - August 24, 2015, 20:28:45 CET [ Project Homepage BibTeX Download ]

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YCML is a Machine Learning framework written in Objective-C, and also available for use in Swift. The following algorithms are currently available:

  • Gradient Descent Back-propagation
  • Resilient Backpropagation (RProp)
  • Extreme Learning Machines (ELM)
  • Forward Selection using Orthogonal Least Squares (for RBF Net)
  • Forward Selection using Orthogonal Least Squares with the PRESS statistic

Where applicable, regularized versions of the algrithms have been implemented.

YCML also contains some optimization algorithms as support for deriving predictive models, although they can be used for any kind of problem:

  • Gradient Descent (Single-Objective, Unconstrained)
  • RProp Gradient Descent (Single-Objective, Unconstrained)
  • NSGA-II (Multi-Objective, Constrained)
Changes to previous version:

Initial Announcement on

BibTeX Entry: Download
Supported Operating Systems: Macosx, Ios
Data Formats: Csv, Matrix, Proprietary
Tags: Regression, Neural Networks, Machine Learning, Ios, Objective C, Osx, Swift
Archive: download here


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