1 # coding=utf-8
 2 import pandas as pd
 3 import numpy as np
 4 from sklearn import cross_validation
 5 import tensorflow as tf
 6 
 7 global flag
 8 flag=0
 9 
10 def DataPreprocessing():
11     abalone = pd.read_csv("train_data.csv", sep=',', header=0, keep_default_na=True)
12     X_train=np.array(abalone.iloc[:,:6])
13     Y_train_=np.array(abalone.iloc[:,6:])
14     print(X_train)
15     Y_train=[]
16     for i in range(len(X_train)):
17 
18         X_train[i][0] = ord(X_train[i][0])-97
19         X_train[i][2] = ord(X_train[i][2])-97
20         X_train[i][4] = ord(X_train[i][4])-97
21 
22     # for i in range (len(X_train)):
23     #     for j in range(6):
24     #         X_train[i][j]=X_train[i][j]-0.0
25     #
26     #X_train.astype(np.float64)
27   #  print(X_train,type(X_train),X_train[0][0],type(X_train[0][0]))
28 
29     #binary classifier
30     for i in range(len(Y_train_)):
31 
32         if Y_train_[i][0]=="draw":
33             Y_train.append(0)
34         else:
35             Y_train.append(1)
36 
37 
38     # multiple classifer
39 
40     return cross_validation.train_test_split(X_train,Y_train,test_size=0.25,random_state=0,stratify=Y_train)
41 
42 
43 def GetInputs():
44     global flag
45     X_train, X_test, Y_train, Y_test = DataPreprocessing()
46 
47     #print(type(X_train),type(X_train[0][0]))
48     #print(X_train)
49     # print(len(X_test))
50     # print(len(Y_train))
51     # print(len(Y_test))
52 
53 
54     #X_train[X_train.isnull().any(axis=1)]
55     #X_train.fillna('',inplace=True)
56 
57     # print(X_train)
58     # print(Y_test)
59 
60     x_train=tf.constant(X_train)
61     y_train=tf.constant(Y_train)
62     x_test=tf.constant(X_test)
63     y_test=tf.constant(Y_test)
64     #
65     # print(x_train)
66     # print(y_train)
67     # print(x_test)
68     # print(y_test)
69 
70     if flag==0:
71         return x_train,y_train
72     else:
73         return x_test,y_test
74 
75 
76 def Main():
77 
78     global flag
79 
80     feature_columns=[tf.contrib.layers.real_valued_column("",dimension=6)]
81 
82     clf=tf.contrib.learn.DNNClassifier(feature_columns=feature_columns,hidden_units=[20,40,20],n_classes=2,model_dir="/home/jiangjing/TensorflowModel/chess")
83 
84     clf.fit(input_fn=GetInputs,steps=2000)
85 
86     flag=1
87     accuracy_score=clf.evaluate(input_fn=GetInputs,steps=1)["accuracy"]
88 
89     print("nTest Accuracy:{0:f}".format(accuracy_score))
90 
91 if __name__ =="__main__":
92     #DataPreprocessing()
93 
94     Main()
95 
96 exit(0)

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