/**
* sdf The test main
*
* @param args ignored
*/
public static void main(String[] args) {
// Instance[] instances = new Instance[100];
// for (int i = 0; i < instances.length; i++) {
// double[] data = new double[2];
// data[0] = Math.sin(i/2.0);
// data[1] = (Math.random() - .5)*2;
// instances[i] = new Instance(data);
// }
DataSet set = new DataSet(trainInstances);
System.out.println("Before randomizing");
System.out.println(set);
// Matrix projection = new RectangularMatrix(new double[][]{ {.6, .6}, {.4, .6}});
Matrix projection = new RectangularMatrix(new double[][] {{.1, .1}, {.1, .1}});
for (int i = 0; i < set.size(); i++) {
Instance instance = set.get(i);
instance.setData(projection.times(instance.getData()));
}
System.out.println("Before ICA");
System.out.println(set);
IndependentComponentAnalysis filter = new IndependentComponentAnalysis(set, 1);
filter.filter(set);
System.out.println("After ICA");
System.out.println(set);
}
public static void main(String[] args) {
Instance[] instances = DataHard.IRIS;
DataSet set = new DataSet(instances);
System.out.println("Before ICA");
System.out.println(set);
int components = 3;
IndependentComponentAnalysis filter = new IndependentComponentAnalysis(set, components);
filter.filter(set);
System.out.println("After ICA");
System.out.println(set);
}