灰色关联度分析

灰⾊关联分析法步骤（python代码实现）

importpandasaspd

importnumpyasnp

#x=ame([[2000,0.732,0.836,0.628,0.743],[2001,0.758,0.883,0.688,0.787],[2002,0.859,0.914,0.781,0.929],[2003,1.0125,1.0440,1.0237,0.984

7],[2004,1.2356,1.1069,1.2833,1.2363],[2005,1.4013,1.2152,1.5405,1.3182]])

#x=_excel('D:')

csv_file="D:"

csv_data=_csv(csv_file,low_memory=Fal)#防⽌弹出警告

x=ame(csv_data)

x=[:,1:].T

#1、数据均值化处理

x_mean=(axis=1)

foriinrange():

[i,:]=[i,:]/x_mean[i]

#[i,:]=[i,:]/x_mean[i]

#2、提取参考队列和⽐较队列

ck=[0,:]

cp=[1:,:]

#⽐较队列与参考队列相减

t=ame()

forjinrange():

temp=([j,:]-ck)

t=(temp,ignore_index=True)

#求最⼤差和最⼩差

mmax=().max().max()

mmin=().min().min()

rho=0.5

#3、求关联系数

ksi=((mmin+rho*mmax)/(abs(t)+rho*mmax))

#4、求关联度

r=(axis=1)/

#5、关联度排序，得到结果r3>r2>r1

result=_values(ascending=Fal)

print(result)