---
metadata:
  - name: generator
    content: Diplodoc Platform v5.54.5
alternate:
  - https://catboost.ai/docs/en/concepts/output-data_feature-analysis_shap-values.md
  - href: en/concepts/output-data_feature-analysis_shap-values.md
    type: text/markdown
    title: Markdown version
  - href: ../llms.txt
    type: text/markdown
    title: llms.txt
---
> **Documentation Index:** Fetch the complete configuration index at https://catboost.ai/docs/en/llms.txt

# ShapValues

#### Contains

A vector $v$ with contributions of each feature to the prediction for every input object and the expected value of the model prediction for the object (average prediction given no knowledge about the object).

<!-- source: en/_includes/work_src/reusage-formats/use-the-shap-package.md -->
Use the [SHAP package](https://github.com/slundberg/shap) to plot the returned values.
<!-- endsource: en/_includes/work_src/reusage-formats/use-the-shap-package.md -->


#### Format

- The rows are sorted in the same order as the order of objects in the input dataset.

- Each row contains information related to one object from the input dataset.

    Format:
    ```
    <contribution of feature 1><\t><contribution of feature 2><\t> .. <\t><contribution of feature N><\t><expected value of the model prediction>
    ```


#### Example

```
-0.0001401524197<\t>0.0001269417313<\t>0.004920700379<\t>0,00490749
```