张量流中的变量类型

我有一个有几个变量类型的模型。

• 布尔标志:0或1
• 分类输入:“AA”,“AB”,“ZZ”-只观察到大约100个值

• cvs文件看起来像

  “bool”,“pos\u float”,“int\u val”,“category\u name”,“output\u score”
  0,1.234,9,“镉”,2
  1,6.836,5,“KF”,6
  0903.836,10,“亚利桑那州”,4
  .....

  import tensorflow as tf
  import pandas as pd
  from sklearn.preprocessing import MinMaxScaler
  
  training_data_df = pd.read_csv("data_training.csv", dtype=float)
  
  X_training = training_data_df.drop('output_score', axis=1).values
  Y_training = training_data_df[['output_score']].values
  
  test_data_df = pd.read_csv("data_test.csv", dtype=float)
  
  X_testing = test_data_df.drop('output_score', axis=1).values
  Y_testing = test_data_df[['output_score']].values
  
  X_scaler = MinMaxScaler(feature_range=(0, 1))
  Y_scaler = MinMaxScaler(feature_range=(0, 1))
  
  X_scaled_training = X_scaler.fit_transform(X_training)
  Y_scaled_training = Y_scaler.fit_transform(Y_training)
  
  X_scaled_testing = X_scaler.transform(X_testing)
  Y_scaled_testing = Y_scaler.transform(Y_testing)
  

  上面的代码将每个变量视为浮点数,并将变量缩放为(0,1)。如何告诉tensorflow变量是整数?如何处理分类变量?