|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).