Module: tf.feature_column

金铨达配资Public API for tf.feature_column namespace.

Functions

bucketized_column(...): Represents discretized dense input.

categorical_column_with_hash_bucket(...)金铨达配资: 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金铨达配资 with in-memory vocabulary.

crossed_column(...)金铨达配资: 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.

make_parse_example_spec(...)金铨达配资: Creates parsing spec dictionary from input feature_columns.

numeric_column(...)金铨达配资: Represents real valued or numerical features.

sequence_categorical_column_with_hash_bucket(...)金铨达配资: 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(...)金铨达配资: 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_embeddings(...): List of dense columns that convert from sparse, categorical input.

weighted_categorical_column(...): Applies weight values to a CategoricalColumn.

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