LASSO_MIN: GLMNET fit with feature selection"

In FRESA.CAD: Feature Selection Algorithms for Computer Aided Diagnosis

Description

Fits a glmnet::cv.glmnet object to the data, and sets the prediction to use the features that created the minimum CV error or one SE.

Usage

	GLMNET(formula = formula,data=NULL,coef.thr=0.001,s="lambda.min",...)
	LASSO_MIN(formula = formula,data=NULL,...)
	LASSO_1SE(formula = formula,data=NULL,...)

Arguments

formula	The base formula to extract the outcome
data	The data to be used for training the KNN method
coef.thr	The threshold for feature selection when alpha < 1.
s	The lambda threshold to be use at prediction and feature selection
...	Parameters to be passed to the cv.glmnet function

Value

fit	The glmnet::cv.glmnet fitted object
s	The s. Set to "lambda.min" or "lambda.1se" for prediction
formula	The formula
outcome	The name of the outcome
usedFeatures	The list of features to be used

Author(s)

Jose G. Tamez-Pena

See Also

glmnet::cv.glmnet

FRESA.CAD documentation built on Jan. 13, 2021, 3:39 p.m.