bst0.3-24 package

Compute upper bound of second derivative of loss

Internal Function

Boosting for Classification and Regression

Function to select number of predictors

Control Parameters for Boosting

Cross-Validation for Boosting

Cross-Validation for one-vs-all AdaBoost with multi-class problem

Cross-Validation for Multi-class Boosting

Cross-Validation for Multi-class Hinge Boosting

Cross-Validation for one-vs-all HingeBoost with multi-class problem

Cross-Validation for Nonconvex Loss Boosting

Cross-Validation for Nonconvex Multi-class Loss Boosting

Compute prediction errors

Generating Three-class Data with 50 Predictors

Multi-class AdaBoost

Boosting for Multi-Classification

Boosting for Multi-class Classification

Multi-class HingeBoost

Find Number of Variables In Multi-class Boosting Iterations

Robust Boosting for Robust Loss Functions

Robust Boosting Path for Nonconvex Loss Functions

Robust Boosting for Multi-class Robust Loss Functions