Description: Train a support vector machine using a simple iterative update procedure first described by Jaakkola, Diekhans and Haussler.

Usage: gist-train-svm [options] -train <train filename> -class <class filename>


Output: A five-column, tab-delimited file. The first two columns are identical to the classification file that was provided as input. Column three contains learned weights for the SVM, each multiplied by the corresponding label. Columns four and five contain the predicted classification and the corresponding discriminant value. This output file is suitable for input to classify.


The following four options control feature selection, which is only available in conjunction with hold-one-out cross-validation. In order to perform feature selection on distinct training and test sets, you must first use fselect to select a feature subset.

The following eight options modify the base kernel function. The operations occur in the order listed below.

Warning messages: