MultivariateRandomForest (version 1.1.5)

Models Multivariate Cases Using Random Forests

Description

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).

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Version

Install

install.packages('MultivariateRandomForest')

Monthly Downloads

246

Version

1.1.5

License

GPL (>= 2)

Maintainer

Raziur Rahman

Last Published

May 1st, 2017

Functions in MultivariateRandomForest (1.1.5)

Node_cost

Information Gain

build_forest_predict

Prediction using Random Forest or Multivariate Random Forest

single_tree_prediction

Prediction of Testing Samples for single tree

split_node

Splitting Criteria of all the nodes of the tree

build_single_tree

Model of a single tree of Random Forest or Multivariate Random Forest

predicting

Prediction of testing sample in a node

CrossValidation

Generate training and testing samples for cross validation

Imputation

Imputation of a numerical vector

splitt2

Split of the Parent node

variable_importance_measure