text: """Census Income utilities.
  
  A collection of constants to be used by the Census Income Classifier.
  """
  
  # Categorical features are assumed to each have a maximum value in the dataset.
  MAX_CATEGORICAL_FEATURE_VALUES = [20]
  
  CATEGORICAL_FEATURE_KEYS = ["Education-Num"]
  
  
  DENSE_FLOAT_FEATURE_KEYS = ["Capital-Gain", "Hours-per-week", "Capital-Loss"]
  
  # Number of buckets used by tf.transform for encoding each feature.
  FEATURE_BUCKET_COUNT = 10
  
  BUCKET_FEATURE_KEYS = ["Age"]
  
  # Number of vocabulary terms used for encoding VOCAB_FEATURES by tf.transform
  VOCAB_SIZE = 200
  
  # Count of out-of-vocab buckets in which unrecognized VOCAB_FEATURES are hashed.
  OOV_SIZE = 10
  
  VOCAB_FEATURE_KEYS = ["Workclass", "Education", "Marital-Status", "Occupation",
                        "Relationship", "Race", "Sex", "Country"]
  
  # Keys
  LABEL_KEY = "Over-50K"
  
  
  def transformed_name(key):
    return key + "_xf"
  