Example usage for weka.filters.unsupervised.attribute RandomProjection setNumberOfAttributes

Introduction

In this page you can find the example usage for weka.filters.unsupervised.attribute RandomProjection setNumberOfAttributes.

Prototype

public void setNumberOfAttributes(int newAttNum) 

Source Link

Document

Sets the number of attributes (dimensions) the data should be reduced to

Usage

From source file:com.sliit.normalize.NormalizeDataset.java

public int whiteningData() {
    System.out.println("whiteningData");

    int nums = 0;
    try {// w  ww .j a v  a 2  s .  co  m

        if (tempFIle != null && tempFIle.exists()) {

            csv.setSource(tempFIle);
        } else {

            csv.setSource(csvFile);
        }
        Instances instances = csv.getDataSet();
        if (instances.numAttributes() > 10) {
            instances.setClassIndex(instances.numAttributes() - 1);
            RandomProjection random = new RandomProjection();
            random.setDistribution(
                    new SelectedTag(RandomProjection.GAUSSIAN, RandomProjection.TAGS_DSTRS_TYPE));
            reducedDiemensionFile = new File(csvFile.getParent() + "/tempwhite.csv");
            if (!reducedDiemensionFile.exists()) {

                reducedDiemensionFile.createNewFile();
            }
            // CSVSaver saver = new CSVSaver();
            /// saver.setFile(reducedDiemensionFile);
            random.setInputFormat(instances);
            //saver.setRetrieval(AbstractSaver.INCREMENTAL);
            BufferedWriter writer = new BufferedWriter(new FileWriter(reducedDiemensionFile));
            for (int i = 0; i < instances.numInstances(); i++) {

                random.input(instances.instance(i));
                random.setNumberOfAttributes(10);
                random.setReplaceMissingValues(true);
                writer.write(random.output().toString());
                writer.newLine();
                //saver.writeIncremental(random.output());
            }
            writer.flush();
            writer.close();
            nums = random.getNumberOfAttributes();
        } else {

            nums = instances.numAttributes();
        }
    } catch (IOException e) {

        log.error("Error occurred:" + e.getMessage());
    } catch (Exception e) {

        log.error("Error occurred:" + e.getMessage());
    }
    return nums;
}

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