GBM.test

Model returned by <code><a rd-options="" href="/link/GBM.train?package=RGBM&version=1.0-7" data-mini-rdoc="RGBM::GBM.train">GBM.train</a></code> function.

model

Input N-by-p feature matrix of unseen samples. Columns correspond to features, rows correspond to samples.

X.test

Input N-element response vector of unseen samples.

Y.test

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.

M.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). See Mall et al (2017) <doi:10.1101/132670>.

Raghvendra Mall

RGBM

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

Khalid Kunji

Melissa O'Neill

GBM.test function

Model returned by <code><a rd-options='' href='GBM.train'>GBM.train</a></code> function.

GBM.test: Test GBM predictor

Description

Usage

Arguments

Value

See Also