# Features and Labels

Features of music could be: intensity, tempo, genre, gender, rhythm and so on. Look at this example. Features are expressed on axes and labels are the answers based on the coordinates of features. In this example, features are numerical values of intensity and tempo. Labels are classification of data points in the chart. Int his case, we have two labels, "She likes those" and "She doesn't like".

![](/files/-M3wY4ewSn93YF3aMvxR)

Here is another example with two features, bumpiness and slope. Labels, in this example, are the colors blue, red and green.

![](/files/-M3wY4ezNBaha8NdTNzb)


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://ondrej-kvasnovsky-2.gitbook.io/handbook-of-hidden-data-scientist-python/machine-learning/supervised-learning/features-and-labels.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.