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Answer: A feature represents data characteristics for prediction, a label is the predicted outcome.
In machine learning, a 'feature' is an individual measurable property or characteristic of a phenomenon being observed. The features are the input data used to make predictions. A 'label' is the outcome or the target variable that we are trying to predict. Therefore, Option A is correct as it accurately describes that a feature is a characteristic of the data used for predictions and a label is the outcome we want to predict.
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What distinguishes a 'feature' from a 'label' in machine learning?
A
A feature represents data characteristics for prediction, a label is the predicted outcome.
B
A label represents data characteristics for prediction, a feature is the predicted outcome.
C
Features and labels are identical in machine learning.
D
A feature is the predicted outcome, a label represents data characteristics for predictions.
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