bucketized_column
bucketized_feature_column = tf.feature_column.bucketized_column(
<br> source_column = numeric_feature_column,
<br> boundaries = [1960, 1980, 2000]
Categorical Column
categorical_column_with_identity
identity_feature_column = tf.feature_column.categorical_column_with_identity(
<br> key='my_feature_b',
<br> num_buckets=4)
categorical_column_with_vocabulary_list
vocabulary_feature_column =
<br> tf.feature_column.categorical_column_with_vocabulary_list(
<br> key="a feature returned by input_fn()",
<br> vocabulary_list=["kitchenware", "electronics", "sports"])
categorical_column_with_vocabulary_file
ocabulary_feature_column =
<br> tf.feature_column.categorical_column_with_vocabulary_file(
<br> key="a feature returned by input_fn()",
<br> vocabulary_file="product_class.txt",
<br> vocabulary_size=3)
categorical_column_with_hash_bucket
hashed_feature_column =
<br> tf.feature_column.categorical_column_with_hash_bucket(
<br> key = "some_feature",
<br> hash_buckets_size = 100) # The number of categories
crossed_column
crossed_lat_lon_fc = tf.feature_column.crossed_column(
<br> [latitude_bucket_fc, longitude_bucket_fc], 5000)
