---
metadata:
  - name: generator
    content: Diplodoc Platform v5.50.3
alternate:
  - https://catboost.ai/docs/en/concepts/python-reference_pool_get_label.md
---
> **Documentation Index:** Fetch the complete configuration index at https://catboost.ai/docs/en/llms.txt

# get_label

<!-- source: en/_includes/work_src/reusage-python/get_label-desc.md -->
Return the value of the label assigned to the input data.
<!-- endsource: en/_includes/work_src/reusage-python/get_label-desc.md -->


## Method call format {#call-format}

```python
get_label()
```

## Type of return value {#output-format}

A one-dimensional array. The type of data in the array depends on the machine learning task being solved:
- Regression , multiregression and ranking  — Numeric values.
- Binary classification — Numeric values.

    The interpretation of numeric values depends on the selected loss function:

    - Logloss — The value is considered a positive class if it is strictly greater than the value of the `` parameter of the loss function. Otherwise, it is considered a negative class.
    - CrossEntropy — The value is interpreted as the probability that the dataset object belongs to the positive class. Possible values are in the range `[0; 1]`.

- Multiclassification — Integers or strings that represents the labels of the classes.