SVMDense Functions - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
9.02
9.01
2.0
1.3
Published
February 2022
Language
English (United States)
Last Update
2022-02-10
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B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢
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).