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

Introduction

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

Prototype

public double[] getCutPoints(int attributeIndex)

Source Link

Document

Gets the cut points for an attribute

Usage

From source file:NaiveBayes.Nilai.java

public Nilai(Instances inst, int i, int j, int classindex) throws Exception {
    Instances newData = new Instances(inst);
    numClass = NaiveBayes.getNumEachClass(newData);
    lower = 0;//from w ww  . jav  a  2  s  . c  o m
    upper = 0;
    kelas = new ArrayList<>();
    //if(newData.instance(i).isMissing(j)) newData.instance(i).setValue(i, "b");
    if (newData.attribute(i).isNumeric()) {
        Discretize f = new Discretize();
        f.setInputFormat(newData);
        newData = Filter.useFilter(newData, f);
        name = newData.attribute(i).value(j);
        if (f.getCutPoints(i) != null) {
            if (j == 0) {
                lower = Double.NEGATIVE_INFINITY;
                upper = f.getCutPoints(i)[j];
            } else {
                if (j != newData.attribute(0).numValues() - 1) {
                    lower = f.getCutPoints(i)[j - 1];
                    upper = f.getCutPoints(i)[j];
                } else {
                    lower = f.getCutPoints(i)[j - 1];
                    upper = Double.POSITIVE_INFINITY;
                }
            }
        } else {
            lower = Double.NEGATIVE_INFINITY;
            upper = Double.POSITIVE_INFINITY;
        }
        for (int k = 0; k < inst.attribute(classindex).numValues(); k++) { //buat nama kelas
            double cnt = 1;
            int countClass = 0;
            for (int l = 0; l < inst.numInstances(); l++) { //jumlah seluruh instances
                double val = inst.get(l).value(i);
                if (countClass <= numClass[k]) {
                    if (inst.attribute(classindex).value(k).equalsIgnoreCase(
                            inst.get(l).toString(classindex).replaceAll("'", ""))) {/*nama kelasnya*/
                        if (val >= lower && val < upper) {//jika ada nilai yang sama pada atribut 
                            //dan kelas yang sama dan nilai dari atribut lebih besar sama dengan lower
                            cnt += 1;
                        }
                        countClass++;
                    }
                } else
                    break;
            }
            kelas.add(new Kelas(newData.attribute(classindex).value(k), cnt));
        }
    } else {
        //System.out.println(newData.attribute(i).value(j).replaceAll("\\s+", ""));
        name = newData.attribute(i).value(j).replaceAll("\\s", "");
        //System.out.println(name);
        //System.out.println(name);
        for (int k = 0; k < inst.attribute(classindex).numValues(); k++) { //buat nama kelas
            double cnt = 1;
            int countClass = 0;
            for (int l = 0; l < inst.numInstances(); l++) { //jumlah seluruh instances
                if (countClass <= numClass[k]) {
                    //System.out.println("with whitespace "+inst.attribute(i).value(j)+"without "+inst.attribute(i).value(j).replaceAll("\\s", "")+"p");
                    //                        System.out.println(inst.get(l).toString(classindex));
                    //System.out.println(inst.attribute(classindex).value(k));
                    if (inst.attribute(classindex).value(k).replaceAll("\\s", "")
                            .equalsIgnoreCase(inst.get(l).toString(classindex).replaceAll("\\s", ""))//nama kelas
                            && inst.attribute(i).value(j).replaceAll("\\s", "").//cek nama atribut
                                    equalsIgnoreCase(inst.get(l).toString(i).replaceAll("\\s", ""))) {
                        //jika ada nilai yang sama pada atribut 
                        //dan kelas yang sama dan nilai dari atribut lebih besar sama dengan lower
                        cnt += 1;
                        countClass++;
                    }
                } else
                    break;
            }
            kelas.add(new Kelas(newData.attribute(classindex).value(k).replaceAll("\\s+", ""), cnt));
        }
    }
}