buildLASSO

An <code>ExprsArray</code> object. The training set.

object

A numeric scalar or character vector. A numeric scalar indicates
the number of top features that should undergo feature selection. A character vector
indicates specifically which features by name should undergo feature selection.
Set <code>top = 0</code> to include all features. A numeric vector can also be used
to indicate specific features by location, similar to a character vector.

Arguments passed to the detailed function.

<code>buildLASSO</code> builds a model using the <code>cv.glmnet</code> function
 from the <code>glmnet</code> package.

Supervised machine learning has an increasingly important role in data
analysis. This package introduces a framework for rapidly building and deploying
supervised machine learning in a high-throughput manner. This package provides a
user-friendly interface that empowers investigators to execute state-of-the-art
binary and multi-class classification, as well as regression, with minimal
programming experience necessary.

buildLASSO: Build LASSO or Ridge Model

Description

Usage

Arguments

Value