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

Introduction

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

Prototype

@Override
public boolean setInputFormat(Instances instanceInfo) throws Exception 

Source Link

Document

Sets the format of the input instances.

Usage

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

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

    int nums = 0;
    try {//w w  w. jav  a 2s.  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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