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. It also provides options for the use of different error estimation approaches of Leaveoneout, Bootstrap, Nfold cross validation and 0.632+Bootstrap along with generation of prediction confidence interval using JackknifeafterBootstrap approach.
Package details 


Author  Raziur Rahman, Ranadip Pal 
Date of publication  20170622 20:36:01 UTC 
Maintainer  Raziur Rahman <[email protected]> 
License  GPL3 
Version  1.1.8 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.