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Label

As explained in Grokking AI Algorithms, Second Edition

A class is a category label assigned to an example in a classification task.

A class label is the category assigned to an example in a classification problem. The example’s attributes provide clues; the label is the answer the classifier must choose. section 8.14

Which kind of device?

Suppose a device has a screen size, weight, and operating system. Those are its attributes. “Tablet,” “laptop,” and “phone” are possible class labels. Classifying the device means choosing among those categories. section 8.15

Ask what kind of answer you need. Deciding whether an animal is a bird is classification: “bird” and “not a bird” are labels. Predicting a diamond’s price from its carat value is regression: the answer is an estimated value, not a class label. section 8.15 section 8.11 section 8.14

How Grokking AI Algorithms, Second Edition covers it

How deep it goes
Defines a label and illustrates category choices, without detailing how a classifier selects one.
Examples
Uses bird-or-not-bird and tablet-laptop-phone decisions, contrasted with predicting diamond prices.
What it assumes
Introduces labels through familiar attributes and categories without requiring formulas or code.
What you can do after
Evaluate/understand whether a proposed answer is a class label or an estimated value.
How it connects
Contrasts classification with regression and connects labels to examples and attributes.

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This explainer was generated by Manning's knowledge graph from the text of Grokking AI Algorithms, Second Edition. The section links point to the parts of the book it draws on.