| title | count_select: Machine Learning Count Mode Feature Selection Transform | |||
|---|---|---|---|---|
| description | Selects the features for which the count of non-default values is greater than or equal to a threshold. | |||
| author | VanMSFT | |||
| ms.author | vanto | |||
| ms.date | 07/15/2019 | |||
| ms.service | sql | |||
| ms.subservice | machine-learning-services | |||
| ms.topic | reference | |||
| keywords |
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| ms.devlang | python | |||
| monikerRange | >=sql-server-2017||>=sql-server-linux-ver15 |
microsoftml.count_select(cols: [list, str], count: int = 1, **kargs)
Selects the features for which the count of non-default values is greater than or equal to a threshold.
When using the count mode in feature selection transform, a feature is
selected if the number of examples have at least the specified count
examples of non-default values in the feature. The count mode feature
selection transform is very useful when applied together with a categorical
hash transform (see also, categorical_hash. The count feature
selection can remove those features generated by hash transform that have no
data in the examples.
Specifies character string or list of the names of the variables to select.
The threshold for count based feature selection. A feature is
selected if and only if at least count examples have non-default
value in the feature. The default value is 1.
Additional arguments sent to compute engine.
An object defining the transform.