adabag-package |
Applies Multiclass AdaBoost.M1, SAMME and Bagging |
adabag |
Applies Multiclass AdaBoost.M1, SAMME and Bagging |
adaboost.M1 |
Applies the AdaBoost.M1 and SAMME algorithms to a data set |
autoprune |
Builds automatically a pruned tree of class 'rpart' |
bagging |
Applies the Bagging algorithm to a data set |
bagging.cv |
Runs v-fold cross validation with Bagging |
boosting |
Applies the AdaBoost.M1 and SAMME algorithms to a data set |
boosting.cv |
Runs v-fold cross validation with AdaBoost.M1 or SAMME |
Ensemble_ranking_IW |
Ensemble methods for ranking data: Item-Weighted Boosting and Bagging Algorithms |
errorevol |
Shows the error evolution of the ensemble |
errorevol_ranking_vector_IW |
Calculate the error evolution and final predictions of an item-weighted ensemble for rankings |
importanceplot |
Plots the variables relative importance |
MarginOrderedPruning.Bagging |
MarginOrderedPruning.Bagging |
margins |
Calculates the margins |
plot.errorevol |
Plots the error evolution of the ensemble |
plot.margins |
Plots the margins of the ensemble |
predict.bagging |
Predicts from a fitted bagging object |
predict.boosting |
Predicts from a fitted boosting object |
prep_data |
Prepare Ranking Data for Item-Weighted Ensemble Algorithm |
simulatedRankingData |
Simulated ranking data |