What are features and labels?

02 · See it in action

A familiar example

For a fictional spam task, features could describe the message text. The label says spam or ordinary according to a defined rule. A field saying “user deleted as spam tomorrow” would not be available when classifying today.

Break it down

1. Identify the input: what information is available?
2. Describe the operation or pattern being used.
3. Identify the output and how you would check it.
4. Name one mistake the system could make.

Change one detail in this example and consider whether the same idea still applies. This helps separate the underlying concept from one specific application.

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