Available Feature Columns
A feature column is a high-level representation of a feature, used by Estimator models such as DNNClassifier.
A feature is any measurable property of the input data, such as a numerical or categorical data.
DeepLearning offers several types of feature columns.
Define a feature which takes a single numeric value, in this case a physical measurement from a flower.
fc ≔ NumericColumn⁡SepalLength,shape=1,datatype=float8
fc≔Feature ColumnNumericColumn(key='SepalLength', shape=(1,), default_value=None, dtype=tf.float64, normalizer_fn=None)
The DeepLearning[FeatureColumn] command was introduced in Maple 2018.
For more information on Maple 2018 changes, see Updates in Maple 2018.
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