CODEWITHSUNDEEP
azuremachine-learningazure-machine-learning-servicecode-documentation
5th
5th

Reputation: 2375

What is the role of feature type in AzureML?

I want to know what is the difference between feature numeric and numeric columns in Azure Machine Learning Studio.

The documentation site states:

Because all columns are initially treated as features, for modules that perform mathematical operations, you might need to use this option to prevent numeric columns from being treated as variables.

But nothing more. Not what a feature is, in which modules you need features. Nothing.

I specifically would like to understand if the clear feature dropdown option in the fields in the edit metadata-module has any effect. Can somebody give me a szenario where this clear feature-operation changes the ML outcome? Thank you

According to the documentation in ought to have an effect:

Use the Fields option if you want to change the way that Azure Machine Learning uses the data in a model.

But what can this effect be? Any example might help

Upvotes: 1

Views: 111

Answers (1)

Vlad Iliescu
Vlad Iliescu

Reputation: 8221

As you suspect, setting a column as feature does have an effect, and it's actually quite important - when training a model, the algorithms will only take into account columns with the feature flag, effectively ignoring the others.

For example, if you have a dataset with columns Feature1, Feature2, and Label and you want to try out just Feature1, you would apply clear feature to the Feature2 column (while making sure that Feature1 has the feature label set, of course).

Upvotes: 1

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