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# Untitled

a guest Aug 19th, 2019 65 Never
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1. import numpy as np
2. import pandas as pd
3. import time
4. from sklearn.ensemble import RandomForestClassifier
5. from sklearn.externals import joblib
6. import scipy.io as sio #存mat
7.
8. start=time.clock()#开始计时
9.
19.
20. xtrain=x_6
21. ytrain=y_6[:,1]
22. xtest=x_7
23. # ytest=y_5[:,1]
24.
25. #RF
26. clf=RandomForestClassifier(n_estimators=50,max_depth=25)
27. clf.fit(xtrain,ytrain)  #.astype('float')强制把类型定义为float，不然dtype=object会报错
28. prediction1=clf.predict_proba(xtest)
29. prediction=np.zeros((prediction1.shape[0],1))
30. for i in range(0,prediction1.shape[0]):
31.     if prediction1[i,1]>0.5:
32.         prediction[i,0]=1
33.     else:
34.         prediction[i,0]=0
35.
36. # 准确率P和召回率R。真正例TP，假正例FP，真反例TN，假反例FN
37. # TP,FP,FN=0,0,0
38. # for i in range(len(prediction)):
39. #     if ytest[i]==1 and prediction[i]==1:
40. #         TP+=1
41. #     if ytest[i]==0 and prediction[i]==1:
42. #         FP+=1
43. #     if ytest[i]==1 and prediction[i]==0:
44. #         FN+=1
45. # P=TP/(TP+FP)
46. # R=TP/(TP+FN)
47.
48. index=np.lexsort([-1*prediction1[:,1]]) #按第二列降序排序
49. prediction2=prediction1[index,:]
50. print("Time used:",time.clock()-start,'s')#计算时间
51. # print('P=',P)
52. # print('R=',R)
53.
54. # '''存mat('文件名.mat', {'文件里变量名': 要存的变量名})'''
55. # sio.savemat('x_4.mat', {'x_4': x_4})
56. # sio.savemat('x_5.mat', {'x_5': x_5})
57. # sio.savemat('y_4.mat', {'y_4': y_4})
58. # sio.savemat('y_5.mat', {'y_5': y_5})
59.
60. # np.savetxt("prediction_7.csv", prediction, delimiter = ',')
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