/** Generate the training sets. */
public void generate() {
sortPoints();
final int start = calculateStartIndex() + 1;
final int setSize = calculateActualSetSize();
final int range = start + setSize - this.predictWindowSize - this.inputWindowSize;
for (int i = start; i < range; i++) {
final BasicMLData input = generateInputNeuralData(i);
final BasicMLData ideal = generateOutputNeuralData(i + this.inputWindowSize);
final BasicMLDataPair pair = new BasicMLDataPair(input, ideal);
super.add(pair);
}
}
/**
* Load from the specified node.
*
* @param pairs The pairs to load.
* @return The EncogPersistedObject that was loaded.
*/
public EncogPersistedObject load(final Element pairs) {
final String name = pairs.getAttribute("name");
final String description = pairs.getAttribute("description");
final BasicNeuralDataSet result = new BasicNeuralDataSet();
result.setName(name);
result.setDescription(description);
for (Node child = pairs.getFirstChild(); child != null; child = child.getNextSibling()) {
if (!(child instanceof Element)) {
continue;
}
final Element node = (Element) child;
if (child.getNodeName().equals(this.pairXML)) {
final NeuralDataPair pair = loadPair(node);
result.add(pair);
}
}
return result;
}