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gcdnet (version 1.0.6)

The (Adaptive) LASSO and Elastic Net Penalized Least Squares, Logistic Regression, Hybrid Huberized Support Vector Machines, Squared Hinge Loss Support Vector Machines and Expectile Regression using a Fast Generalized Coordinate Descent Algorithm

Description

Implements a generalized coordinate descent (GCD) algorithm for computing the solution paths of the hybrid Huberized support vector machine (HHSVM) and its generalizations. Supported models include the (adaptive) LASSO and elastic net penalized least squares, logistic regression, HHSVM, squared hinge loss SVM and expectile regression.

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Install

install.packages('gcdnet')

Monthly Downloads

353

Version

1.0.6

License

GPL (>= 2)

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Last Published

August 14th, 2022

Functions in gcdnet (1.0.6)

coef

Extract Model Coefficients
gcdnet

Fits the regularization paths for large margin classifiers
print.gcdnet

Print a gcdnet object
predict.gcdnet

Make predictions from a "gcdnet" object
coef.gcdnet

Get coefficients or make coefficient predictions from a "gcdnet" object.
FHT

FHT data introduced in Friedman et al. (2010).
predict

Model predictions
predict.cv.gcdnet

Make predictions from a "cv.gcdnet" object.
cv.gcdnet

Cross-validation for gcdnet
plot.cv.gcdnet

Plot the cross-validation curve produced by cv.gcdnet
coef.cv.gcdnet

Get coefficients or make coefficient predictions from a "cv.gcdnet" object.
plot.gcdnet

Plot coefficients from a "gcdnet" object