RGBM.test

This function tests a regression model for a given <code>X.test</code> feature matrix, <code>Y.test</code> response vector, and working parameters.

Provides an implementation of Regularized LS-TreeBoost & LAD-TreeBoost algorithm for Regulatory Network inference from any type of expression data (Microarray/RNA-seq etc).

Raghvendra Mall

RGBM

LS-TreeBoost and LAD-TreeBoost for Gene Regulatory Network
Reconstruction

Khalid Kunji

Melissa O'Neill

RGBM.test function

<dl> <dt>model</dt>
<dd>Model returned by <code>RGBM.train</code> function.</dd> <dt>X.test</dt>
<dd>Input S-by-P feature matrix of unseen samples. Columns correspond to features, rows correspond to samples.</dd> <dt>Y.test</dt>
<dd>Input S-element response vector of unseen samples.</dd> <dt>M.test</dt>
<dd>Number of extensions of boosting model to take when predicting response. Must be not greater than <code>M.train</code> used when training boosting model.</dd></dl>

Arguments

Raghvendra Mall &lt;raghvendra5688@gmail.com&gt;

Author

Test rgbm predictor — RGBM.test

<dl>

 <dt>model</dt>
<dd>Model returned by <code>RGBM.train</code> function.</dd>

 <dt>X.test</dt>
<dd>Input S-by-P feature matrix of unseen samples. Columns correspond to features, rows correspond to samples.</dd>

 <dt>Y.test</dt>
<dd>Input S-element response vector of unseen samples.</dd>

 <dt>M.test</dt>
<dd>Number of extensions of boosting model to take when predicting response. Must be not greater than <code>M.train</code> used when training boosting model.</dd>

</dl>

RGBM.test: Test rgbm predictor

Description

Usage

Value

Arguments

Author