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>.

Getting started

Package details

AuthorKyle Peterson [aut, cre]
MaintainerKyle Peterson <[email protected]>
LicenseGPL-2
Version1.2.1
URL http://mlf-project.us/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("mlf")

Try the mlf package in your browser

Any scripts or data that you put into this service are public.

mlf documentation built on June 25, 2018, 9:01 a.m.