7.00.02 - Ensemble Methods - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Content Type
Programming Reference
User Guide
Publication ID
B700-1022-700K
Language
English (United States)
Last Update
2018-04-17
Ensemble Methods Functions
Function Description
Random Forest Functions Create a predictive model based on a combination of the classification and regression trees (CART) algorithm for training decision trees and the ensemble learning method of bagging. The Random Forest functions are Forest_Drive, Forest_Predict, and Forest_Analyze.
Single Decision Tree Functions Create a predictive model that has a single decision tree. The Single Decision Tree functions are Single_Tree_Drive and Single_Tree_Predict.
AdaBoost Functions Create a predictive model based on the AdaBoost algorithm. The AdaBoost functions are AdaBoost_Drive and AdaBoost_Predict.
XGBoost Functions Create a predictive model based on the GradientBoost algorithm. The XGBoost functions are XGBoost_Drive and XGBoost_Predict.