In learning algorithms and statistical classification, a random forest is an ensemble classifier that consists in many decision trees.
I'm trying to train several random forests (for regression) to have them compete and see which feature selection and which …
r parallel-processing random-forest doparallel parallel-foreachI've been dealing with some extremely imbalanced data and I would like to use stratified sampling to created more balanced …
r random-forest r-caretIs it possible to train a model in Xgboost that have multiple continuous outputs (multi regression)? What would be the …
machine-learning random-forest xgboostI used RandomForest for a regression problem. I used importance(rf,type=1) to get the %IncMSE for the variables and …
r statistics random-forest predictionThere is absolutely helpful class GridSearchCV in scikit-learn to do grid search and cross validation, but I don't want to …
python scikit-learn random-forest grid-searchI am trying to obtain the variable importance of a rf model in any way. This is the approach I …
r random-forest r-caretFirst, I have checked the different posts concerning this error and none of them can solve my issue. So I …
python scikit-learn random-forest valueerrorThe help page for randomforest::randomforest() says: "classwt - Priors of the classes. Need not add up to one. Ignored …
r random-forestIs it possible to apply RandomForests to very small datasets? I have a dataset with many variables but only 25 observation …
machine-learning random-forest sample-sizeI originally had a data frame composed of 12 columns in N rows. The last column is my class (0 or 1). I …
r random-forest