DeepLearning
FeatureColumn
Feature Column
Description
Available Feature Columns
Examples
Compatibility
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.
BucketizedColumn
CategoricalColumn
NumericColumn
Define a feature which takes a single numeric value, in this case a physical measurement from a flower.
with⁡DeepLearning:
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.
See Also
DNNClassifier
Download Help Document
What kind of issue would you like to report? (Optional)