Public API for tf.feature_column namespace.
Functions
bucketized_column(...)
: Represents discretized dense input bucketed by boundaries
.
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.
sequence_categorical_column_with_hash_bucket(...)
: A sequence of categorical terms where ids are set by hashing.
sequence_categorical_column_with_identity(...)
: Returns a feature column that represents sequences of integers.
sequence_categorical_column_with_vocabulary_file(...)
: A sequence of categorical terms where ids use a vocabulary file.
sequence_categorical_column_with_vocabulary_list(...)
: A sequence of categorical terms where ids use an in-memory list.
sequence_numeric_column(...)
: Returns a feature column that represents sequences of numeric data.
shared_embedding_columns(...)
: List of dense columns that convert from sparse, categorical input.
weighted_categorical_column(...)
: Applies weight values to a CategoricalColumn
.