Integrated Prediction using Uni-Variate and Multivariate Random Forests

Documentation for package ‘IntegratedMRF’ version 1.1.9

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