R packages by razrahman

MultivariateRandomForest - Models Multivariate Cases Using Random Forests

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>.

Last updated 8 years ago

cpp

2.97 score 2 stars 3 dependents 26 scripts 271 downloads

IntegratedMRF - Integrated Prediction using Uni-Variate and Multivariate Random Forests

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 Leave-one-out, Bootstrap, N-fold cross validation and 0.632+Bootstrap along with generation of prediction confidence interval using Jackknife-after-Bootstrap approach.

Last updated 7 years ago

cpp

1.26 score 18 scripts 239 downloads