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mlf (version 1.2.1)

Machine Learning Foundations

Description

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. Szkely GJ, Rizzo ML, Bakirov NK. (2007). . Reshef DN, Reshef YA, Finucane HK, Grossman SR, McVean G, Turnbaugh PJ, Lander ES, Mitzenmacher M, Sabeti PC. (2011). .

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Version

Install

install.packages('mlf')

Monthly Downloads

150

Version

1.2.1

License

GPL-2

Maintainer

Kyle Peterson

Last Published

June 25th, 2018

Functions in mlf (1.2.1)

get_mse

Mean Squared Error
distcorr

Distance Correlation
get_bias

Bias
entropy

Entropy
bvto

Bias-Variance Trade-Off
boot

Bootstrap Confidence Intervals via Resampling
get_var

Variance
kld

Kullback-Leibler Divergence
jointentropy

Joint Entropy
perm

Permutation Test
mi

Mutual Information
mic

Maximal Information Criterion