IntegratedMRF (1.0)

Integrated Prediction using Univariate and Multivariate Random Forests.

An implementation of a framework for drug sensitivity prediction from various genetic characterizations using ensemble approaches. Random Forests or Multivariate Random Forest predictive models can be generated from each genetic characterization that are then combined using a Least Square Regression approach. IntegratedMRF also provides options for the use of different error estimation approaches of Leave-one-out, Bootstrap, Re-substitution and 0.632Bootstrap along with generation of prediction confidence interval using Jackknife-after-Bootstrap approach.

Maintainer: Raziur Rahman
Author(s): Raziur Rahman <>

License: GPL-3

Uses: bootstrap, ggplot2, limSolve

Released about 3 years ago.