A Copula Based Approach for Design of Multivariate Random Forests for Drug Sensitivity Prediction.

ABSTRACT: Modeling sensitivity to drugs based on genetic characterizations is a significant challenge in the area of systems medicine. Ensemble based approaches such as Random Forests have been shown to perform well in both individual sensitivity prediction studies and team science based prediction challenges. However, Random Forests generate a deterministic predictive model for each drug based on the genetic characterization of the cell lines and ignores the relationship between different drug sensitivities during model generation. This application motivates the need for generation of multivariate ensemble learning techniques that can increase prediction accuracy and improve variable importance ranking by incorporating the relationships between different output responses. In this article, we propos

SUBMITTER: Haider S 

PROVIDER: S-EPMC4684346 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature