1.1 - 8.10 - SVMDense Functions - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Teradata Vantage
Release Number
October 2019
Content Type
Programming Reference
Publication ID
English (United States)
Function Description
SVMDense (ML Engine) Takes training data and builds predictive model in binary format.
SVMDensePredict (ML Engine) Uses model to predict class of each sample in test data set.
SVMDenseSummary (ML Engine) Displays readable information about model.

The SVMDense and SVMDensePredict functions are designed for input in dense format; that is, each table column contains values of a single attribute and there is a single row for each sample (observation).

This implementation of SVMDense functions includes a linear SVM based on a Pegasos algorithm and a non-linear SVM based on the Hash-SVM model described in the paper "Hash-SVM: Scalable Kernel Machines for Large-Scale Visual Classification," by Yadong Mu, Gang Hua, Wei Fan, and Shih-Fu Chang (http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6909525).