Description:

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 mloss.org.

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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