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])-9719         X_train[i][2] = ord(X_train[i][2])-9720         X_train[i][4] = ord(X_train[i][4])-9721 22     # for i in range (len(X_train)):23     #     for j in range(6):24     #         X_train[i][j]=X_train[i][j]-0.025     #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 classifier30     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 classifer39 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 flag45     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_train72     else:73         return x_test,y_test74 75 76 def Main():77 78     global flag79 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=187     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)