/**
* initialize various variables before starting the actual optimizer
*
* @param data data set used for learning
* @throws Exception if something goes wrong
*/
protected void init(Instances data) throws Exception {
super.init(data);
// init error cache
m_error = new double[m_nInstances];
for (int i = 0; i < m_nInstances; i++) {
m_error[i] = -m_target[i];
}
}
/**
* Parses a given list of options.
*
* <p>
* <!-- options-start -->
* Valid options are:
*
* <p>
*
* <pre> -P <double>
* The epsilon for round-off error.
* (default 1.0e-12)</pre>
*
* <pre> -L <double>
* The epsilon parameter in epsilon-insensitive loss function.
* (default 1.0e-3)</pre>
*
* <pre> -W <double>
* The random number seed.
* (default 1)</pre>
*
* <!-- options-end -->
*
* @param options the list of options as an array of strings
* @throws Exception if an option is not supported
*/
public void setOptions(String[] options) throws Exception {
String tmpStr;
tmpStr = Utils.getOption('P', options);
if (tmpStr.length() != 0) {
setEpsilon(Double.parseDouble(tmpStr));
} else {
setEpsilon(1.0e-12);
}
super.setOptions(options);
}
/**
* wrap up various variables to save memeory and do some housekeeping after optimization has
* finished.
*
* @throws Exception if something goes wrong
*/
protected void wrapUp() throws Exception {
m_error = null;
super.wrapUp();
}
