SimpleKMeans cluster classification example using Weka library.

MyKMeansClusterer.java

import weka.core.Instance;
import weka.core.Instances;
import weka.core.converters.ArffLoader;
import weka.clusterers.SimpleKMeans;
import weka.clusterers.ClusterEvaluation;

import java.io.File;
import java.io.FileWriter;

/**
  * Simple K-Means Clusterer using Weka library
  *
  * @Author Faisal Wirakusuma, University of Manchester
  *
  */
public class MyKMeansClusterer{

   /**
    * Expects an ARFF file as first argument.
    *
    * @param args        the commandline arguments
    * @throws Exception  if something goes wrong
    */
 	public static void main(String[] args) throws Exception{

 		//load data from arguments
 		ArffLoader loader = new ArffLoader();
 		loader.setFile(new File(args[0]));
 		Instances structure = loader.getDataSet();

 		FileWriter writer = new FileWriter("lab2_2-ii_result.csv");
 		writer.append("NumClusters");
 		writer.append(',');
 		writer.append("SSE");
 		writer.append('\n');
 		for(int i = 2; i<=50; i++){
	 		SimpleKMeans mySKMeans = new SimpleKMeans();
	 		mySKMeans.setPreserveInstancesOrder(true);
	 		mySKMeans.setMaxIterations(500);
	 		mySKMeans.setNumClusters(i);
	 		mySKMeans.setSeed(10);
	 		mySKMeans.buildClusterer(structure);
	 		//ClusterEvaluation eval = new ClusterEvaluation();
	 		//eval.setClusterer(mySKMeans);
	 		//eval.evaluateClusterer(new Instances(structure));

	 		//System.out.println(structure);

	 		//System.out.println("SSE "+i+" : "+mySKMeans.getSquaredError());
	 		writer.append(i+"");
	 		writer.append(',');
	 		writer.append(mySKMeans.getSquaredError()+"");
	 		writer.append('\n');
	 		mySKMeans = null;
	 	}
	 	writer.flush();
	 	writer.close();
 	} 


}

To compile : javac -cp weka.jar MyKMeansClusterer.java
To run : java -cp .:weka.jar MyKMeansClusterer baskball.arff

Hi,
When I am trying to run this, it is saying weka.core package does not exist..not sure, how to get this work.Any help would be appreciated.