medusa.georgios.ClusteringAlgorithms

Class KMeans2

java.lang.Object

medusa.georgios.ClusteringAlgorithms.KMeans2

public class KMeans2
extends java.lang.Object

Implements the k-means algorithm

Constructor Summary

Constructors

Constructor and Description
KMeans2(int k, BasicGraph g)
KMeans2(int k, java.util.List kMeansPoints) Returns a new instance of kMeans algorithm
KMeans2(int k, java.lang.String inputFileName) Returns a new instance of kMeans algorithm

Method Summary

Modifier and Type	Method and Description
medusa.georgios.ClusteringAlgorithms.cluster	getCluster(int index) Returns the specified cluster by index
java.util.Map<java.lang.String,java.lang.Integer>	getClusterMap()
java.util.Vector	getDataPoints() Returns the data points
int	getK() Returns the value of k
java.lang.String	getReport()
int	getSmallestClusterSize()
static void	main(java.lang.String[] args) Main method -- to test the kMeans class
void	readData() Reads the input data from the file and stores the data points in the vector
void	runKMeans() Runs the k-means algorithm over the data set
java.lang.String	Save_To_File(java.lang.String filename)
void	Save_To_File(java.lang.String filename, java.lang.String information)
java.lang.String	toString() Returns the string output of the data points

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

KMeans2

public KMeans2(int k,
               java.lang.String inputFileName)

Returns a new instance of kMeans algorithm

Parameters:

k - number of clusters

inputFileName - name of the file containing input data

KMeans2

public KMeans2(int k,
               BasicGraph g)

KMeans2

public KMeans2(int k,
               java.util.List kMeansPoints)

Returns a new instance of kMeans algorithm

Parameters:

k - number of clusters

kMeansPoints - List containing objects of type kMeansPoint

Method Detail

readData

public void readData()
              throws java.io.IOException

Reads the input data from the file and stores the data points in the vector

Throws:

java.io.IOException

runKMeans

public void runKMeans()

Runs the k-means algorithm over the data set

Save_To_File

public java.lang.String Save_To_File(java.lang.String filename)

getK

public int getK()

Returns the value of k

Returns:

the value of k

getCluster

public medusa.georgios.ClusteringAlgorithms.cluster getCluster(int index)

Returns the specified cluster by index

Parameters:

index - index of the cluster to be returned

Returns:

return the specified cluster by index

toString

public java.lang.String toString()

Returns the string output of the data points

Overrides:

toString in class java.lang.Object

Returns:

the string output of the data points

getDataPoints

public java.util.Vector getDataPoints()

Returns the data points

Returns:

the data points

getClusterMap

public java.util.Map<java.lang.String,java.lang.Integer> getClusterMap()

getReport

public java.lang.String getReport()

Save_To_File

public void Save_To_File(java.lang.String filename,
                         java.lang.String information)

getSmallestClusterSize

public int getSmallestClusterSize()

main

public static void main(java.lang.String[] args)

Main method -- to test the kMeans class

Parameters:

args - command line arguments