Models Multivariate Cases Using Random Forests
Prediction using Random Forest or Multivariate Random Forest
Model of a single tree of Random Forest or Multivariate Random Forest
Generate training and testing samples for cross validation
Imputation of a numerical vector
Information Gain
Prediction of testing sample in a node
Prediction of Testing Samples for single tree
Splitting Criteria of all the nodes of the tree
Split of the Parent node
Calculates variable Importance of a Regression Tree Model
Models and predicts multiple output features in single random forest considering the linear relation among the output features, see details in Rahman et al (2017)<doi:10.1093/bioinformatics/btw765>.