/** Writes the example set into the given output stream. */
public void writeSupportVectors(ObjectOutputStream out) throws IOException {
out.writeInt(getNumberOfSupportVectors());
out.writeDouble(b);
out.writeInt(dim);
if ((meanVarianceMap == null) || (meanVarianceMap.size() == 0)) {
out.writeUTF("noscale");
} else {
out.writeUTF("scale");
out.writeInt(meanVarianceMap.size());
Iterator i = meanVarianceMap.keySet().iterator();
while (i.hasNext()) {
Integer index = (Integer) i.next();
MeanVariance meanVariance = meanVarianceMap.get(index);
out.writeInt(index.intValue());
out.writeDouble(meanVariance.getMean());
out.writeDouble(meanVariance.getVariance());
}
}
for (int e = 0; e < train_size; e++) {
if (alphas[e] != 0.0d) {
out.writeInt(atts[e].length);
for (int a = 0; a < atts[e].length; a++) {
out.writeInt(index[e][a]);
out.writeDouble(atts[e][a]);
}
out.writeDouble(alphas[e]);
out.writeDouble(ys[e]);
}
}
}
/**
* Creates a fresh example set of the given size from the RapidMiner example reader. The alpha
* values and b are zero, the label will be set if it is known.
*/
public SVMExamples(
com.rapidminer.example.ExampleSet exampleSet,
Attribute labelAttribute,
Map<Integer, MeanVariance> meanVariances) {
this(exampleSet.size(), 0.0d);
this.meanVarianceMap = meanVariances;
Iterator<com.rapidminer.example.Example> reader = exampleSet.iterator();
Attribute idAttribute = exampleSet.getAttributes().getId();
int exampleCounter = 0;
while (reader.hasNext()) {
com.rapidminer.example.Example current = reader.next();
Map<Integer, Double> attributeMap = new LinkedHashMap<Integer, Double>();
int a = 0;
for (Attribute attribute : exampleSet.getAttributes()) {
double value = current.getValue(attribute);
if (!com.rapidminer.example.Tools.isDefault(attribute.getDefault(), value)) {
attributeMap.put(a, value);
}
if ((a + 1) > dim) {
dim = (a + 1);
}
a++;
}
atts[exampleCounter] = new double[attributeMap.size()];
index[exampleCounter] = new int[attributeMap.size()];
Iterator<Map.Entry<Integer, Double>> i = attributeMap.entrySet().iterator();
int attributeCounter = 0;
while (i.hasNext()) {
Map.Entry<Integer, Double> e = i.next();
Integer indexValue = e.getKey();
Double attributeValue = e.getValue();
index[exampleCounter][attributeCounter] = indexValue.intValue();
double value = attributeValue.doubleValue();
MeanVariance meanVariance = meanVarianceMap.get(indexValue);
if (meanVariance != null) {
if (meanVariance.getVariance() == 0.0d) {
value = 0.0d;
} else {
value = (value - meanVariance.getMean()) / Math.sqrt(meanVariance.getVariance());
}
}
atts[exampleCounter][attributeCounter] = value;
attributeCounter++;
}
if (labelAttribute != null) {
double label = current.getValue(labelAttribute);
if (labelAttribute.isNominal()) {
ys[exampleCounter] = (label == labelAttribute.getMapping().getPositiveIndex() ? 1 : -1);
} else {
ys[exampleCounter] = label;
}
}
if (idAttribute != null) {
ids[exampleCounter] = current.getValueAsString(idAttribute);
}
exampleCounter++;
}
}
