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metadata:
  - name: generator
    content: Diplodoc Platform v5.52.0
alternate:
  - https://catboost.ai/docs/en/features/object-importances-calcution.md
  - href: en/features/object-importances-calcution.md
    type: text/markdown
    title: Markdown version
  - href: ../llms.txt
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    title: llms.txt
---
> **Documentation Index:** Fetch the complete configuration index at https://catboost.ai/docs/en/llms.txt

# Object importances

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CatBoost provides the following types of object importances calculation:
- [Average](https://catboost.ai/docs/en/concepts/ostr.md)
- [PerObject](https://catboost.ai/docs/en/concepts/ostr.md)
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Choose the implementation for more details.
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## Python package

Classes:

### [CatBoost](https://catboost.ai/docs/en/concepts/python-reference_catboost.md)

**Class purpose**

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Training and applying models.
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**Method**

 [get_object_importance](https://catboost.ai/docs/en/concepts/python-reference_catboost_get_object_importance.md)

### [CatBoostClassifier](https://catboost.ai/docs/en/concepts/python-reference_catboostclassifier.md)

**Class purpose**

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Training and applying models.
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**Method**

 [get_object_importance](https://catboost.ai/docs/en/concepts/python-reference_catboostclassifier_get_object_importance.md)

### [CatBoostRegressor](https://catboost.ai/docs/en/concepts/python-reference_catboostregressor.md)

**Class purpose**

<!-- source: en/_includes/work_src/reusage-python/purpose.md -->
Training and applying models.
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**Method**

 [get_object_importance](https://catboost.ai/docs/en/concepts/python-reference_catboostregressor_get_object_importance.md)

## R package

**Method**

[catboost.get_object_importance](https://catboost.ai/docs/en/concepts/r-reference_catboost-get_object_importance.md)

**Purpose**

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Calculate the effect of objects from the train dataset on the optimized metric values for the objects from the input dataset:
- Positive values reflect that the optimized metric increases.
- Negative values reflect that the optimized metric decreases.
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## Command-line version

**Command**

[catboost ostr](https://catboost.ai/docs/en/concepts/cli-reference_ostr-calc.md)

**Purpose**

<!-- source: en/_includes/work_src/reusage/ostr__desc-main.md -->
Calculate the effect of objects from the training dataset on the optimized metric values for the objects from the validation dataset:
- Positive values reflect that the optimized metric increases.
- Negative values reflect that the optimized metric decreases.
The higher the deviation from 0, the bigger the impact that an object has on the optimized metric.
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