# Integrated Prediction using Uni-Variate and Multivariate Random Forests

## Documentation for package ‘IntegratedMRF’ version 1.1.9

- DESCRIPTION file.

## Help Pages

build_forest_predict | Prediction using Random Forest or Multivariate Random Forest
build_single_tree | Model of a single tree of Random Forest or Multivariate Random Forest
Combination | Weights for combination of predictions from different data subtypes using Least Square Regression based on various error estimation techniques
CombPredict | Integrated Prediction of Testing samples using Combination Weights from integrated RF or MRF model
CombPredictSpecific | Prediction for testing samples using specific combination weights from integrated RF or MRF model
CrossValidation | Generate training and testing samples for cross validation
Dream_Dataset | NCI-Dream Drug Sensitivity Prediction Challenge Dataset
error_calculation | Error calculation for integrated model
Imputation | Imputation of a numerical vector
IntegratedPrediction | Integrated Prediction of Testing samples from integrated RF or MRF model
Node_cost | Information Gain
predicting | Prediction of testing sample in a node
single_tree_prediction | Prediction of Testing Samples for single tree
splitt | Split of the Parent node
split_node | Splitting Criteria of all the nodes of the tree