GLMNET

LASSO_MIN

LASSO_1SE

GLMNET_ELASTICNET_MIN

GLMNET_ELASTICNET_1SE

GLMNET_RIDGE_MIN

GLMNET_RIDGE_1SE

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

Model_Generation

Contains a set of utilities for building and testing statistical models (linear, logistic,ordinal or COX) for Computer Aided Diagnosis/Prognosis applications. Utilities include data adjustment, univariate analysis, model building, model-validation, longitudinal analysis, reporting and visualization.

Jose Tamez-Pena

FRESA.CAD

Feature Selection Algorithms for Computer Aided Diagnosis

GLMNET function

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

Arguments

Author

GLMNET fit with feature selection" — GLMNET

<dl>

	<dt>formula</dt>
<dd>The base formula to extract the outcome</dd>

	<dt>data</dt>
<dd>The data to be used for training the KNN method</dd>

	<dt>coef.thr</dt>
<dd>The threshold for feature selection when alpha &lt; 1.</dd>

	<dt>s</dt>
<dd>The lambda threshold to be use at prediction and feature selection</dd>

	<dt>...</dt>
<dd>Parameters to be passed to the cv.glmnet function</dd>

</dl>

GLMNET fit with feature selection"

GLMNET: GLMNET fit with feature selection"

Description

Usage

Value

Arguments

Author

See Also