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

Introduction

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

Prototype

public int getNumberOfAttributes() 

Source Link

Document

Gets the current number of attributes (dimensionality) to which the data will be reduced to.

Usage

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

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

    int nums = 0;
    try {//  w  w w .j av a 2  s .c  om

        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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