Example usage for weka.filters.unsupervised.attribute Discretize input

Introduction

In this page you can find the example usage for weka.filters.unsupervised.attribute Discretize input.

Prototype

@Override
public boolean input(Instance instance) 

Source Link

Document

Input an instance for filtering.

Usage

From source file:NaiveBayesPckge.NaiveBayesMain.java

public static void addNewInstance(Instances instances) throws Exception {
    Scanner scan = new Scanner(System.in);
    ArrayList<Attribute> atts = new ArrayList<Attribute>();
    ArrayList<String> classVal = new ArrayList<String>();
    int nConclus = instances.attribute(instances.numAttributes() - 1).numValues();
    int numAttribut = instances.numAttributes();

    //buat nambah kesimpulan. Misal T dan F
    for (int i = 0; i < nConclus; i++) {
        classVal.add(instances.attribute(instances.numAttributes() - 1).value(i));
    }/*from   ww w.  java 2 s  .c o  m*/

    //buat nambahin attribut
    for (int i = 0; i < numAttribut - 1; i++) {
        atts.add(new Attribute(instances.attribute(i).name()));
    }
    atts.add(new Attribute(instances.attribute(numAttribut - 1).name(), classVal));

    double[] attValues = new double[numAttribut];
    System.out.print("Masukkan nilai : ");
    for (int i = 0; i < numAttribut - 1; i++) {
        attValues[i] = scan.nextDouble();
    }
    Discretize discretize = new Discretize();
    String s = scan.nextLine();

    Instance instance = new DenseInstance(1.0, attValues);

    instance.setDataset(instances);

    discretize.setInputFormat(instances);
    discretize.input(instance);

    int classify1 = (int) naive.classifyInstance(instance);
    System.out.print("Prediction Class : ");
    System.out.println(classVal.get(classify1));
}

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