How do features in Machine Learning differ from targets, and why are both necessary?
- Features and targets are the same
- Features are input; Targets are predictions
- Features are predictions; Targets are input
- None of these definitions are correct
Features are the input variables used to make predictions, while targets are the values the model is trying to predict. Both are necessary for supervised learning, where features are used to predict the corresponding targets.
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