Defined in tensorflow/_api/v1/feature_column/__init__.py.
Public API for tf.feature_column namespace.
Functions
bucketized_column(...): Represents discretized dense input.
categorical_column_with_hash_bucket(...): Represents sparse feature where ids are set by hashing.
categorical_column_with_identity(...): A CategoricalColumn that returns identity values.
categorical_column_with_vocabulary_file(...): A CategoricalColumn with a vocabulary file.
categorical_column_with_vocabulary_list(...): A CategoricalColumn with in-memory vocabulary.
crossed_column(...): Returns a column for performing crosses of categorical features.
embedding_column(...): DenseColumn that converts from sparse, categorical input.
indicator_column(...): Represents multi-hot representation of given categorical column.
input_layer(...): Returns a dense Tensor as input layer based on given feature_columns.
linear_model(...): Returns a linear prediction Tensor based on given feature_columns.
make_parse_example_spec(...): Creates parsing spec dictionary from input feature_columns.
numeric_column(...): Represents real valued or numerical features.
shared_embedding_columns(...): List of dense columns that convert from sparse, categorical input.
weighted_categorical_column(...): Applies weight values to a CategoricalColumn.