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main.py
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main.py
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#_*_coding:utf-8_*_
import pandas as pd
import loaddata,classify,datasetplot,testresult
import numpy as np
import matplotlib.pyplot as plt
def main(filename,ratio,k):
trainset=pd.DataFrame()
testset=pd.DataFrame()
dataset=pd.DataFrame()
trainset,testset,dataset=loaddata.loadDataset(filename,ratio,trainset,testset)
#datasetplot.datasetplot(dataset)
#datasetplot.datasetplot(trainset)
#datasetplot.datasetplot(testset)
result=classify.classify(trainset,testset,k)
#print 'The result is:\n',result
#print 'The result accuracy rate is:',testresult.testresult(testset,result),'%'
return testresult.testresult(testset,result)
if __name__=="__main__":
#resultset=pd.DataFrame()
accuracy=[]
for i in range(1):
#for j in range(20):
accuracy.append(main('iris.data',0.67,i+1))
mean=np.array(accuracy).mean()
print mean
#print accuracy
#plt.plot(accuracy)
#plt.show()
#resultset['accuracy rate']=accuracy
#resultset['ratio']=[(float(j)+1)/20 for j in range(20)]
#resultset['k value']=[i+1 for i in range(20)]
#resultset.plot()
#print resultset
#return accuracy