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METODY SZTUCZNEJ INTELIGENCJI

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ZADANIE I

Odczyt danych z pliku irys.tab zapisanych w formacie tab z wykorzystaniem bibliotek rseslib.

http://rsproject.mimuw.edu.pl./components.html

http://logic.mimuw.edu.pl/~rses/

http://rsproject.mimuw.edu.pl/

http://tunedit.org/

http://tunedit.org/challenge/RSCTC-2010-A?m=overview

/*

* To change this template, choose Tools | Templates

* and open the template in the editor.

*

*

* http://rsproject.mimuw.edu.pl./components.html

*

* http://logic.mimuw.edu.pl/~rses/

*

* http://rsproject.mimuw.edu.pl/

*

* http://tunedit.org/

*

* http://tunedit.org/challenge/RSCTC-2010-A?m=overview

*

*

*/

package javaapplication3;

import java.util.logging.Level;

import java.util.logging.Logger;

import rseslib.example.*;

import rseslib.structure.attribute.formats.HeaderFormatException;

import rseslib.structure.data.formats.DataFormatException;

import rseslib.system.*;

import rseslib.structure.*;

import rseslib.processing.clustering.*;

import rseslib.structure.attribute.*;

import rseslib.structure.data.*;

import rseslib.structure.table.*;

import rseslib.system.progress.*;

import java.io.*;

/**

*

* @author student

*/

public class Main {

/**

* @param args the command line arguments

*/

public static void main(String[] args) throws DataFormatException {

// TODO code application logic here

try{

Header hdr = new ArrayHeader(new File("D:/data/irys.tab"));

DoubleDataTable table = new ArrayListDoubleDataTable(

new File("D:/data/irys.tab"),

hdr,

new StdOutProgress());

}

catch (HeaderFormatException ex) {

System.out.println(ex.getMessage());

}

catch (BadHeaderException ex) {

System.out.println(ex.getMessage());

}

catch (InterruptedException ex) {

System.out.println(ex.getMessage());

}

catch(IOException ex){

System.out.println(ex.getMessage());

}

}

}

ZADANIE II

Odczyt danych z pliku iris.arff zapisanych w formacie arff z wykorzystaniem bibliotek weka.

/*

* To change this template, choose Tools | Templates

* and open the template in the editor.

*/

import weka.core.Instances;

import java.io.*;

import java.io.IOException;

import weka.filters.Filter;

import weka.classifiers.meta.FilteredClassifier;

import weka.classifiers.trees.J48;

import weka.filters.unsupervised.attribute.Remove;

import weka.classifiers.Evaluation;

import java.util.Random;

/**

*

* @author student

*/

public class Main {

public static void printDatasetINFO(Instances data) {

System.out.println("Dataset has been read....");

System.out.println("Number of objects " + data.numInstances());

System.out.println("Number of attributes " + data.numAttributes());

System.out.println("Number of classes " + data.numClasses());

}

public static void setDatasetClassified(J48 tree) {

try{

// load unlabeled data

Instances unlabeled = new Instances(

new BufferedReader(

new FileReader("D:\\data\\iris.arff")));

// set class attribute

unlabeled.setClassIndex(unlabeled.numAttributes() - 1);

// create copy

Instances labeled = new Instances(unlabeled);

// label instances

for (int i = 0; i < unlabeled.numInstances(); i++) {

double clsLabel = tree.classifyInstance(unlabeled.instance(i));

labeled.instance(i).setClassValue(clsLabel);

}

// save labeled data

BufferedWriter writer = new BufferedWriter( new FileWriter("D:\\data\\iris2.arff"));

writer.write(labeled.toString());

writer.newLine();

writer.flush();

writer.close();

}

catch(IOException ex) {

System.out.println(ex.getMessage());

}

catch(Exception ex) {

System.out.println(ex.getMessage());

}

}

/**

* @param args the command line arguments

*/

public static void main(String[] args) {

// TODO code application logic here

try{

BufferedReader reader1 = new BufferedReader( new FileReader("D:\\data\\iris.arff"));

Instances data = new Instances(reader1);

reader1.close();

data.setClassIndex(data.numAttributes() - 1);

BufferedReader reader2 = new BufferedReader( new FileReader("D:\\data\\iris.arff"));

Instances test = new Instances(reader2);

reader2.close();

test.setClassIndex(data.numAttributes() - 1);

printDatasetINFO(data);

// create new instance of scheme

weka.classifiers.functions.SMO scheme = new weka.classifiers.functions.SMO();

// set options

scheme.setOptions(weka.core.Utils.splitOptions("-C 1.0 -L 0.0010 -P 1.0E-12 -N 0 -V -1 -W 1 -K \"weka.classifiers.functions.supportVector.PolyKernel -C 250007 -E 1.0\""));

String[] options = new String[2];

options[0] = "-R"; // "range"

options[1] = "1"; // first attribute

Remove remove = new Remove(); // new instance of filter

remove.setOptions(options); // set options

remove.setInputFormat(data); // inform filter about dataset **AFTER** setting options

Instances newData = Filter.useFilter(data, remove); // apply filter

printDatasetINFO(newData);

Remove rm = new Remove();

rm.setAttributeIndices("1"); // remove 1st attribute

// classifier

J48 j48 = new J48();

j48.setUnpruned(true); // using an unpruned J48

// meta-classifier

FilteredClassifier fc = new FilteredClassifier();

fc.setFilter(rm);

fc.setClassifier(j48);

// train and make predictions

fc.buildClassifier(data);

for (int i = 0; i < test.numInstances(); i++) {

double pred = fc.classifyInstance(test.instance(i));

System.out.print("ID: " + test.instance(i).value(0));

System.out.print(", actual: " + test.classAttribute().value((int) test.instance(i).classValue()));

System.out.println(", predicted: " + test.classAttribute().value((int) pred));

}

options = new String[1];

options[0] = "-U"; // unpruned tree

J48 tree = new J48(); // new instance of tree

tree.setOptions(options); // set the options

tree.buildClassifier(data); // build classifier

Evaluation eval = new Evaluation(newData);

eval.crossValidateModel(tree, newData, 10, new Random(1));

eval = new Evaluation(data);

eval.evaluateModel(tree, test);

System.out.println(eval.toSummaryString("\nResults\n======\n", false));

options = new String[2];

options[0] = "-t";

options[1] = "D:\\data\\iris.arff";

System.out.println(Evaluation.evaluateModel(new J48(), options));

setDatasetClassified(tree);

}

catch(IOException ex){

}

catch(Exception ex){

}

}

}