Example usage for weka.classifiers.functions SMO setFilterType

Introduction

In this page you can find the example usage for weka.classifiers.functions SMO setFilterType.

Prototype

public void setFilterType(SelectedTag newType) 

Source Link

Document

Sets how the training data will be transformed.

Usage

From source file:jjj.asap.sas.models1.job.BuildRBFKernelModels.java

License:Open Source License

@Override
protected void run() throws Exception {

    // validate args
    if (!Bucket.isBucket("datasets", inputBucket)) {
        throw new FileNotFoundException(inputBucket);
    }// w  ww.ja  va2  s . com
    if (!Bucket.isBucket("models", outputBucket)) {
        throw new FileNotFoundException(outputBucket);
    }

    // init multi-threading
    Job.startService();
    final Queue<Future<Object>> queue = new LinkedList<Future<Object>>();

    // get the input from the bucket
    List<String> names = Bucket.getBucketItems("datasets", this.inputBucket);
    for (String dsn : names) {

        SMO smo = new SMO();
        smo.setFilterType(new SelectedTag(SMO.FILTER_NONE, SMO.TAGS_FILTER));
        smo.setBuildLogisticModels(true);
        RBFKernel kernel = new RBFKernel();
        kernel.setGamma(0.05);
        smo.setKernel(kernel);

        AttributeSelectedClassifier asc = new AttributeSelectedClassifier();
        asc.setEvaluator(new InfoGainAttributeEval());
        Ranker ranker = new Ranker();
        ranker.setThreshold(0.01);
        asc.setSearch(ranker);
        asc.setClassifier(smo);

        queue.add(Job.submit(new ModelBuilder(dsn, "InfoGain-SMO-RBFKernel", asc, this.outputBucket)));
    }

    // wait on complete
    Progress progress = new Progress(queue.size(), this.getClass().getSimpleName());
    while (!queue.isEmpty()) {
        try {
            queue.remove().get();
        } catch (Exception e) {
            Job.log("ERROR", e.toString());
        }
        progress.tick();
    }
    progress.done();
    Job.stopService();

}

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From source file:org.uclab.mm.icl.llc.config.RecognizerType.java

License:Apache License

/**
 * Returns the corresponding recognizer//from  w  w  w. j a  v a  2  s.com
 * @param rec recognizer type to return
 * @param userID user ID to set
 * @return instance of the corresponding recognizer
 */
public LLCRecognizer getRecognizer(long userID) {

    RecognizerType rec = this.values()[value];
    switch (rec) {
    case SER:
        String[] labels = { "Anger", "Happiness", "Sadness" };
        String path = FileUtil.getRootPath() + "/training/modeldataV2.7.txt";
        SMO svm = new SMO(); // Define Classifier with Weka
        try {
            svm.setOptions(weka.core.Utils.splitOptions(
                    "-C 1.0 -L 0.0010 -P 1.0E-12 -N 1 -V -1 -W 1 -K \"weka.classifiers.functions.supportVector.RBFKernel -C 250007 -G 0.01\""));
            svm.setFilterType(new SelectedTag(SMO.FILTER_STANDARDIZE, SMO.TAGS_FILTER));
        } catch (Exception e) {
            e.printStackTrace();
        }
        ExtClassification classifier = new ExtClassification(path, 78 * 2, labels, svm);
        AudioEmotionRecognizer aer = new AudioEmotionRecognizer(classifier, path, userID);

        return aer;
    case ER:
        return new AudioEmotionRecognizerV(userID);
    case IAR:
        return new InertialActivityRecognizer(userID);
    case VAR:
        return new VideoActivityRecognizer(userID);
    case LR:
        //get user loc coord / label with userID by restful service
        return new GPSLocationRecognizer(userID);
    case FR:
        return new FoodRecognizer(userID);
    }
    return null;
}

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