lars - Least Angle Regression, Lasso and Forward Stagewise
Efficient procedures for fitting an entire lasso sequence with the cost of a single least squares fit. Least angle regression and infinitesimal forward stagewise regression are related to the lasso, as described in the paper below.
Last updated 2 years ago
6 stars 6.33 score 0 dependencies 78 dependentsgam - Generalized Additive Models
Functions for fitting and working with generalized additive models, as described in chapter 7 of "Statistical Models in S" (Chambers and Hastie (eds), 1991), and "Generalized Additive Models" (Hastie and Tibshirani, 1990).
Last updated 2 months ago
4 stars 5.13 score 3 dependencies 59 dependentsmda - Mixture and Flexible Discriminant Analysis
Mixture and flexible discriminant analysis, multivariate adaptive regression splines (MARS), BRUTO, and vector-response smoothing splines. Hastie, Tibshirani and Friedman (2009) "Elements of Statistical Learning (second edition, chap 12)" Springer, New York.
Last updated 1 years ago
2 stars 4.29 score 2 dependencies 15 dependentssvmpath - The SVM Path Algorithm
Computes the entire regularization path for the two-class svm classifier with essentially the same cost as a single SVM fit.
Last updated 4 years ago
1.45 score 1 dependencies 2 dependentsISLR - Data for an Introduction to Statistical Learning with Applications in R
We provide the collection of data-sets used in the book 'An Introduction to Statistical Learning with Applications in R'.
Last updated 3 years ago
4 stars 1.31 score 0 dependencies 3 dependentssparsenet - Fit Sparse Linear Regression Models via Nonconvex Optimization
Efficient procedure for fitting regularization paths between L1 and L0, using the MC+ penalty of Zhang, C.H. (2010)<doi:10.1214/09-AOS729>. Implements the methodology described in Mazumder, Friedman and Hastie (2011) <DOI: 10.1198/jasa.2011.tm09738>. Sparsenet computes the regularization surface over both the family parameter and the tuning parameter by coordinate descent.
Last updated 7 months ago
2 stars 1.00 score 3 dependencies 1 dependentsgamsel - Fit Regularization Path for Generalized Additive Models
Using overlap grouped-lasso penalties, 'gamsel' selects whether a term in a 'gam' is nonzero, linear, or a non-linear spline (up to a specified max df per variable). It fits the entire regularization path on a grid of values for the overall penalty lambda, both for gaussian and binomial families. See <doi:10.48550/arXiv.1506.03850> for more details.
Last updated 2 months ago
2 stars 0.49 score 6 dependenciesISLR2 - Introduction to Statistical Learning, Second Edition
We provide the collection of data-sets used in the book 'An Introduction to Statistical Learning with Applications in R, Second Edition'. These include many data-sets that we used in the first edition (some with minor changes), and some new datasets.
Last updated 2 years ago
2 stars 0.23 score 0 dependenciesProDenICA - Product Density Estimation for ICA using Tilted Gaussian Density Estimates
A direct and flexible method for estimating an ICA model. This approach estimates the densities for each component directly via a tilted Gaussian. The tilt functions are estimated via a GAM Poisson model. Details can be found in "Elements of Statistical Learning (2nd Edition)" in Section 14.7.4.
Last updated 3 years ago
1 stars 0.09 score 4 dependencies