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Customized training is a simple technique for transductive learning, when the test covariates are kn...
fits the primal graphical lasso, via one-at-a-time
Fits the Fused Lasso Latent Feature model, which is used for modeling multi-sample aCGH data to iden...
Functions for fitting and working with generalized additive models, as described in chapter 7 of "St...
Using overlap grouped lasso penalties, gamsel selects whether a term in a gam is nonzero, linear, or...
Group-Lasso INTERaction-NET. Fits linear pairwise-interaction models that satisfy strong hierarchy: ...
Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for l...
A path-following algorithm for L1 regularized generalized
linear models and Cox proportional ...
The collection of datasets used in the book "An Introduction to Statistical Learning with Applicatio...
Fit multinomial logistic regression with a penalty on the nuclear norm of the estimated regression c...
A direct and flexible method for estimating an ICA model. This approach estimates the densities for ...
Fit a regularized generalized linear model via penalized maximum likelihood. The model is fit for a...
Sparsenet uses the MC+ penalty of Zhang. It computes the regularization surface over both the family...
L2 penalized logistic regression for both continuous and
discrete predictors, with forward st...
Computes the entire regularization path for the two-class
svm classifier with essentially the...
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Mee Young Park