1.1 - 8.10 - Predictive Modeling - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.1
8.10
Release Date
October 2019
Content Type
Programming Reference
Publication ID
B700-4003-079K
Language
English (United States)
Function Description
KNN (ML Engine) Uses the kNN algorithm to classify new objects based on their proximity to already-classified objects.
AdaBoost Functions (ML Engine) Create a predictive model based on the AdaBoost algorithm.
Cox Functions (ML Engine) Cox proportional hazards model functions.
Decision Forest Functions (ML Engine) 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.
Decision Tree Functions (ML Engine) Create a predictive model that has a single decision tree.
Generalized Linear Model (GLM) Functions (ML Engine) Perform linear regression analysis for distribution functions using a user-specified distribution family and link function.
Least Angle Regression (LAR) Functions (ML Engine) Selects the most important variables one by one and fit the coefficients dynamically.
Linear Regression Functions (ML Engine) Create and use linear regression model.
Naive Bayes Functions (ML Engine) Train a Naive Bayes classification model and use the model to predict new outcomes.
Support Vector Machine (SVM) Functions (ML Engine) Creates a predictive model based on a support vector machine, using a linear or nonlinear kernel.
XGBoost Functions (ML Engine) Create a predictive model based on the GradientBoost algorithm.