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mlf: Machine Learning Foundations

Offers a gentle introduction to machine learning concepts for practitioners with a statistical pedigree: decomposition of model error (bias-variance trade-off), nonlinear correlations, information theory and functional permutation/bootstrap simulations. Székely GJ, Rizzo ML, Bakirov NK. (2007). <doi:10.1214/009053607000000505>. Reshef DN, Reshef YA, Finucane HK, Grossman SR, McVean G, Turnbaugh PJ, Lander ES, Mitzenmacher M, Sabeti PC. (2011). <doi:10.1126/science.1205438>.

Version: 1.2.1
Imports: stats, utils
Published: 2018-06-25
DOI: 10.32614/CRAN.package.mlf
Author: Kyle Peterson [aut, cre]
Maintainer: Kyle Peterson <petersonkdon at gmail.com>
License: GPL-2
URL: http://mlf-project.us/
NeedsCompilation: no
CRAN checks: mlf results

Documentation:

Reference manual: mlf.pdf

Downloads:

Package source: mlf_1.2.1.tar.gz
Windows binaries: r-devel: mlf_1.2.1.zip, r-release: mlf_1.2.1.zip, r-oldrel: mlf_1.2.1.zip
macOS binaries: r-release (arm64): mlf_1.2.1.tgz, r-oldrel (arm64): mlf_1.2.1.tgz, r-release (x86_64): mlf_1.2.1.tgz, r-oldrel (x86_64): mlf_1.2.1.tgz
Old sources: mlf archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mlf to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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