DenseSVM Functions - Aster Analytics

Teradata AsterĀ® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Language
English (United States)
Last Update
2018-04-17
dita:mapPath
uce1497542673292.ditamap
dita:ditavalPath
AA-notempfilter_pdf_output.ditaval
dita:id
B700-1022
lifecycle
previous
Product Category
Software

The DenseSVMTrainer and DenseSVMPredictor 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 DenseSVM function 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).