net.sf.javaml.tools.data.FileHandler Java Examples

The following examples show how to use net.sf.javaml.tools.data.FileHandler. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example #1
Source File: JMLNeurophSample.java    From NeurophFramework with Apache License 2.0 5 votes vote down vote up 
public static void main(String[] args) {
    try {
        //create jml dataset
        Dataset jmlDataset = FileHandler.loadDataset(new File("datasets/iris.data"), 4, ",");

        // normalize dataset
        NormalizeMidrange nmr=new NormalizeMidrange(0,1);
        nmr.build(jmlDataset);         
        nmr.filter(jmlDataset);
        
        //print data as read from file
        System.out.println(jmlDataset);

        //convert jml dataset to neuroph
        DataSet neurophDataset = JMLDataSetConverter.convertJMLToNeurophDataset(jmlDataset, 4, 3);
        
        //convert neuroph dataset to jml
        Dataset jml = JMLDataSetConverter.convertNeurophToJMLDataset(neurophDataset);

        //print out both to compare them
        System.out.println("Java-ML data set read from file");
        printDataset(jmlDataset);
        System.out.println("Neuroph data set converted from Java-ML data set");
        printDataset(neurophDataset);
        System.out.println("Java-ML data set reconverted from Neuroph data set");
        printDataset(jml);

        System.out.println("JMLNeuroph classifier test");
        //test NeurophJMLClassifier
        testJMLNeurophClassifier(jmlDataset);

    } catch (Exception ex) {
        Logger.getLogger(JMLNeurophSample.class.getName()).log(Level.SEVERE, null, ex);
    }

}
Example #2
Source File: JavaMLClusterers.java    From apogen with Apache License 2.0 5 votes vote down vote up 
public static LinkedHashMap<Integer, LinkedList<String>> runKmedoid(String filename, String numClusters,
		boolean distance) throws IOException {

	LinkedHashMap<Integer, LinkedList<String>> output = null;
	Clusterer c = new KMedoids(Integer.parseInt(numClusters), 500, new EuclideanDistance());

	// if (distance) {
	//// c = new KMedoidsDistance(Integer.parseInt(numClusters), 500,
	//// new EuclideanDistance());
	// c = new KMedoids(Integer.parseInt(numClusters), 500, new
	// EuclideanDistance());
	// } else {
	// c = new KMedoids(Integer.parseInt(numClusters), 500,
	// new EuclideanDistance());
	// }

	Dataset data = FileHandler.loadDataset(new File(filename), 0, ",");

	Dataset[] clusters = c.cluster(data);

	output = convert(clusters);

	return output;

}