/*
?*?SimpleFuzzyCMeans.java
?*?
?*?本算法是在weka自帶的SimpleKMeans算法的基礎上修改而成的
?*?在Eclipse平臺下運行實現。
?*?
?*?本算法保留了SimpleKMeans算法的基本構架，
?*?對其算法的核心代碼進行了修改，
?*?將核心代碼換為模糊C均值聚類算法。
?*?
?*?SimpleKMeans算法支持Euclidean和Manhattan距離，
?*?本算法出于簡便，只支持Euclidean距離。
?*?
?*?算法關于數據的預處理以及程序結果的輸出采用SimpleKMeans算法的代碼，
?*?并進行了少量的修改（主要是參數項的設置）。
?*?
?*?程序運行前先修改weka.gui包中的文件GenericobjectEditor.pros，
?*?在其語句“#?Lists?the?Clusterers?I?want?to?choose?from“下
?*?加入語句“weka.clusterers.SimpleFuzzyCMeans\“，然后保存。
?*?
?*?運行weka.gui包中的文件GUIChooser.java，
?*?便可打開weka的圖形界面，然后選擇數據，
?*?在其聚類算法模塊下選擇SimpleFuzzyCMeans，
?*?對算法的參數進行適當的設置，
?*?即可運行模糊C均值聚類算法。
?*
?*/

package?weka.clusterers;

import?weka.classifiers.rules.DecisionTableHashKey;
import?weka.core.Attribute;
import?weka.core.Capabilities;
import?weka.core.DistanceFunction;
import?weka.core.EuclideanDistance;
import?weka.core.Instance;
import?weka.core.Instances;
import?weka.core.Option;
import?weka.core.Utils;
import?weka.core.WeightedInstancesHandler;
import?weka.core.Capabilities.Capability;
import?weka.filters.Filter;
import?weka.filters.unsupervised.attribute.ReplaceMissingValues;

import?java.util.Enumeration;
import?java.util.HashMap;
import?java.util.Random;
import?java.util.Vector;

public?class?SimpleFuzzyCMeans?extends?RandomizableClusterer?implements
		NumberOfClustersRequestable?WeightedInstancesHandler?{

	/**
	?*?for?serialization
	?*/
	static?final?long?serialVersionUID?=?3235809600124455123L;

	/**
	?*?replace?missing?values?in?training?instances
	?*/
	private?ReplaceMissingValues?m_ReplaceMissingFilter;

	/**
	?*?number?of?clusters?to?generate
	?*/
	private?int?m_NumClusters?=?2;

	/**
	?*?實例數據
	?*/
	private?Instances?instances;

	/**
	?*?holds?the?cluster?centroids
	?*/
	private?Instances?m_ClusterCentroids;

	/**
	?*?Holds?the?standard?deviations?of?the?numeric?attributes?in?each?cluster
	?*/
	private?Instances?m_ClusterStdDevs;

	/**
	?*?For?each?cluster?holds?the?frequency?counts?for?the?values?of?each
	?*?nominal?attribute
	?*/
	private?int[][][]?m_ClusterNominalCounts;
	private?int[][]?m_ClusterMissingCounts;

	/**
	?*?Stats?on?the?full?data?set?for?comparison?purposes?In?case?the?attribute
	?*?is?numeric?the?value?is?the?mean?if?is?being?used?the?Euclidian?distance
	?*?and?if?the?attribute?is?nominal?then?it‘s?mode?is?saved
	?*/
	private?double[]?m_FullMeansOrModes;
	private?double[]?m_FullStdDevs;
	private?int[][]?m_FullNominalCounts;
	private?int[]?m_FullMissingCounts;

	/**
	?*?Display?standard?deviations?for?numeric?atts
	?*/
	private?boolean?m_displayStdDevs?=?true;

	/**
	?*?Replace?missing?values?globally?
	?*/
	private?boolean?m_dontReplaceMissing?=?false;

	/**
	?*?The?number?of?instances?in?each?cluster
	?*/
	private?int[]?m_ClusterSizes;

	/**
	?*?隸屬度矩陣
	?*/
	private?double[][]?membershipMatrix;

	/**
	?*?模糊系數
	?*/
	private?double?fuzzyCoefficient?=?（double）?2.0;

	/**
	?*?定義誤差精度
	?*/