Description Usage Arguments Value Note See Also
Wrapper function to perform random forest regression with randomForest
that trains a model on training set and then predicts on test set for multiple tasks.
1 | predictorRF(patientsTrain, patientsTest, response, ntree = 500)
|
patientsTrain |
Matrix of training descriptors, of dimension |
patientsTest |
Matrix of test descriptors, of dimension |
response |
Matrix of observed toxicity values, of dimension |
ntree |
Number of trees to grow a random forest. Default is 500. All other arguments are taken by default implementation of |
A matrix of predicted toxicity values, of dimension m x t
, for the m
test patients responding to the t
drugs.
Prediction is made per task with no special treatment for multitask learning, nor are task features needed.
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