28 citations · 29 across the 3 of their papers we have counts for
3 papers
Covariance regression with random forests
Cansu Alakus, Denis Larocque, Aurelie Labbe
Capturing the conditional covariances or correlations among the elements of a multivariate response vector based on covariates is important to various fields including neuroscience…
RFpredInterval: An R Package for Prediction Intervals with Random Forests and Boosted Forests
Cansu Alakus, Denis Larocque, Aurelie Labbe
Like many predictive models, random forests provide point predictions for new observations. Besides the point prediction, it is important to quantify the uncertainty in the predict…
Conditional canonical correlation estimation based on covariates with random forests
Cansu Alakus, Denis Larocque, Sebastien Jacquemont +5
Investigating the relationships between two sets of variables helps to understand their interactions and can be done with canonical correlation analysis (CCA). However, the correla…