readme.txt

FCM算法是一种基于划分的聚类算法

请运行程序，并在程序所在文件夹下面创建文本文件：datain.txt和paramOut.txt，文件的详细说明见下面。程序的运行没有可视的界面，运行完毕之后会在该文件夹下面产生center.txt和matrix.txt两个文件，其中center.txt为聚类的中心，matrix.txt为隶属度矩阵。在运行本程序之前，先参考一下FCM聚类算法介绍.doc

输入文件：
datain.txt
paramOut.txt
其中，datain.txt表示输入的样本数据
paramOut.txt表示输入的聚类参数。
1168
5
4
2
500
.1
其中1168表示样本点的个数，5表示输入样本的维数，4表示要聚类的类别数，2表示m参数，500表示最大的循环次数，0.1表示聚类的精度。

输出文件
center.txt表示聚类的中心，
2.235158,2.216862,2.259246,2.179756,14.487826,
2.011866,1.990132,1.986863,1.928874,9.807125,
2.159366,2.154501,2.137472,2.051354,21.563583,
1.777569,1.751310,1.846922,1.769809,2.417483,
一个行表示一个类中心，一个列表示一个维度。

matrix.txt
0.063055,0.129468,0.029966,0.777510,
0.011885,0.030029,0.004839,0.953246,
0.012895,0.035797,0.004966,0.946342,
0.982582,0.010087,0.005656,0.001675,
0.017419,0.047566,0.006742,0.928273,
0.113058,0.570329,0.031078,0.285535,
0.623048,0.305760,0.040247,0.030945,
0.081656,0.862810,0.014612,0.040923,
0.911263,0.040214,0.040591,0.007932,
0.006618,0.017270,0.002653,0.973458,
0.004695,0.012169,0.001894,0.981242,
0.004305,0.011272,0.001727,0.982697,
0.006983,0.017895,0.002830,0.972292,
一个行表示一个样本属于四个类的隶属度向量，一个列表示属于第几类的隶属度。

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