Index

A

• adabag packages
  • using / Using the adabag and gbm packages
• adaptive boosting / Adaptive boosting
• Adaptive boosting algorithm
  • about / Why does boosting work?
  • working / Why does boosting work?
• additive effect / Exponential smoothing state space model
• advantages, extreme gradient boosting implementation
  • parallel computing / The xgboost package
  • regularization / The xgboost package
  • cross-validation / The xgboost package
  • pruning / The xgboost package
  • missing values / The xgboost package
  • saving and reloading / The xgboost package
  • cross platform / The xgboost package
• amyotrophic lateral sclerosis (ALS) / Squared-error loss function
• area under curve (AUC) / Complementary statistical tests
• auto-correlation function (ACF) / Core concepts and metrics
• Auto-regressive Integrated Moving Average (ARIMA) models / Auto-regressive Integrated Moving Average (ARIMA) models

B

• bagging
  • comparing...