# evidently.metric\_preset

### class ClassificationPreset(columns: Optional\[List\[str]] = None, probas\_threshold: Optional\[float] = None, k: Optional\[int] = None)

Bases: `MetricPreset`

Metrics preset for classification performance.

Contains metrics:

* ClassificationQualityMetric
* ClassificationClassBalance
* ClassificationConfusionMatrix
* ClassificationQualityByClass

#### Attributes:

     **columns : Optional\[List\[str]]**

     **k : Optional\[int]**

     **probas\_threshold : Optional\[float]**

#### Methods:

     **generate\_metrics(data:** [**InputData**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.metrics#evidently.metrics.base_metric.InputData)**, columns:** [**DatasetColumns**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.utils#evidently.utils.data_operations.DatasetColumns)**)**

### class DataDriftPreset(columns: Optional\[List\[str]] = None, drift\_share: float = 0.5, stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, cat\_stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, num\_stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, per\_column\_stattest: Optional\[Dict\[str, Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]]] = None, stattest\_threshold: Optional\[float] = None, cat\_stattest\_threshold: Optional\[float] = None, num\_stattest\_threshold: Optional\[float] = None, per\_column\_stattest\_threshold: Optional\[Dict\[str, float]] = None)

Bases: `MetricPreset`

Metric Preset for Data Drift analysis.

Contains metrics:

* DatasetDriftMetric
* DataDriftTable

#### Attributes:

     **cat\_stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

     **cat\_stattest\_threshold : Optional\[float]**

     **columns : Optional\[List\[str]]**

     **drift\_share : float**

     **num\_stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

     **num\_stattest\_threshold : Optional\[float]**

     **per\_column\_stattest : Optional\[Dict\[str, Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]]**

     **per\_column\_stattest\_threshold : Optional\[Dict\[str, float]]**

     **stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

     **stattest\_threshold : Optional\[float]**

#### Methods:

     **generate\_metrics(data:** [**InputData**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.metrics#evidently.metrics.base_metric.InputData)**, columns:** [**DatasetColumns**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.utils#evidently.utils.data_operations.DatasetColumns)**)**

### class DataQualityPreset(columns: Optional\[List\[str]] = None)

Bases: `MetricPreset`

Metric preset for Data Quality analysis.

Contains metrics:

* DatasetSummaryMetric
* ColumnSummaryMetric for each column
* DatasetMissingValuesMetric
* DatasetCorrelationsMetric
* **Parameters**

  `columns` – list of columns for analysis.

#### Attributes:

     **columns : Optional\[List\[str]]**

#### Methods:

     **generate\_metrics(data:** [**InputData**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.metrics#evidently.metrics.base_metric.InputData)**, columns:** [**DatasetColumns**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.utils#evidently.utils.data_operations.DatasetColumns)**)**

### class RegressionPreset(columns: Optional\[List\[str]] = None)

Bases: `MetricPreset`

Metric preset for Regression performance analysis.

Contains metrics:

* RegressionQualityMetric
* RegressionPredictedVsActualScatter
* RegressionPredictedVsActualPlot
* RegressionErrorPlot
* RegressionAbsPercentageErrorPlot
* RegressionErrorDistribution
* RegressionErrorNormality
* RegressionTopErrorMetric
* RegressionErrorBiasTable

#### Attributes:

     **columns : Optional\[List\[str]]**

#### Methods:

     **generate\_metrics(data:** [**InputData**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.metrics#evidently.metrics.base_metric.InputData)**, columns:** [**DatasetColumns**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.utils#evidently.utils.data_operations.DatasetColumns)**)**

### class TargetDriftPreset(columns: Optional\[List\[str]] = None, stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, cat\_stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, num\_stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, per\_column\_stattest: Optional\[Dict\[str, Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]]] = None, stattest\_threshold: Optional\[float] = None, cat\_stattest\_threshold: Optional\[float] = None, num\_stattest\_threshold: Optional\[float] = None, per\_column\_stattest\_threshold: Optional\[Dict\[str, float]] = None)

Bases: `MetricPreset`

Metric preset for Target Drift analysis.

Contains metrics:

* ColumnDriftMetric - for target and prediction if present in datasets.
* ColumnValuePlot - if task is regression.
* ColumnCorrelationsMetric - for target and prediction if present in datasets.
* TargetByFeaturesTable

#### Attributes:

     **cat\_stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

     **cat\_stattest\_threshold : Optional\[float]**

     **columns : Optional\[List\[str]]**

     **num\_stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

     **num\_stattest\_threshold : Optional\[float]**

     **per\_column\_stattest : Optional\[Dict\[str, Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]]**

     **per\_column\_stattest\_threshold : Optional\[Dict\[str, float]]**

     **stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

     **stattest\_threshold : Optional\[float]**

#### Methods:

     **generate\_metrics(data:** [**InputData**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.metrics#evidently.metrics.base_metric.InputData)**, columns:** [**DatasetColumns**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.utils#evidently.utils.data_operations.DatasetColumns)**)**

## Submodules

## classification\_performance module <a href="#module-evidently.metric_preset.classification_performance" id="module-evidently.metric_preset.classification_performance"></a>

### class ClassificationPreset(columns: Optional\[List\[str]] = None, probas\_threshold: Optional\[float] = None, k: Optional\[int] = None)

Bases: `MetricPreset`

Metrics preset for classification performance.

Contains metrics:

* ClassificationQualityMetric
* ClassificationClassBalance
* ClassificationConfusionMatrix
* ClassificationQualityByClass

#### Attributes:

&#x20;    **columns : Optional\[List\[str]]**

&#x20;    **k : Optional\[int]**

&#x20;    **probas\_threshold : Optional\[float]**

#### Methods:

&#x20;    **generate\_metrics(data:** [**InputData**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.metrics#evidently.metrics.base_metric.InputData)**, columns:** [**DatasetColumns**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.utils#evidently.utils.data_operations.DatasetColumns)**)**

## data\_drift module <a href="#module-evidently.metric_preset.data_drift" id="module-evidently.metric_preset.data_drift"></a>

### class DataDriftPreset(columns: Optional\[List\[str]] = None, drift\_share: float = 0.5, stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, cat\_stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, num\_stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, per\_column\_stattest: Optional\[Dict\[str, Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]]] = None, stattest\_threshold: Optional\[float] = None, cat\_stattest\_threshold: Optional\[float] = None, num\_stattest\_threshold: Optional\[float] = None, per\_column\_stattest\_threshold: Optional\[Dict\[str, float]] = None)

Bases: `MetricPreset`

Metric Preset for Data Drift analysis.

Contains metrics:

* DatasetDriftMetric
* DataDriftTable

#### Attributes:

&#x20;    **cat\_stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

&#x20;    **cat\_stattest\_threshold : Optional\[float]**

&#x20;    **columns : Optional\[List\[str]]**

&#x20;    **drift\_share : float**

&#x20;    **num\_stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

&#x20;    **num\_stattest\_threshold : Optional\[float]**

&#x20;    **per\_column\_stattest : Optional\[Dict\[str, Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]]**

&#x20;    **per\_column\_stattest\_threshold : Optional\[Dict\[str, float]]**

&#x20;    **stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

&#x20;    **stattest\_threshold : Optional\[float]**

#### Methods:

&#x20;    **generate\_metrics(data:** [**InputData**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.metrics#evidently.metrics.base_metric.InputData)**, columns:** [**DatasetColumns**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.utils#evidently.utils.data_operations.DatasetColumns)**)**

## data\_quality module <a href="#module-evidently.metric_preset.data_quality" id="module-evidently.metric_preset.data_quality"></a>

### class DataQualityPreset(columns: Optional\[List\[str]] = None)

Bases: `MetricPreset`

Metric preset for Data Quality analysis.

Contains metrics:

* DatasetSummaryMetric
* ColumnSummaryMetric for each column
* DatasetMissingValuesMetric
* DatasetCorrelationsMetric
* **Parameters**

  `columns` – list of columns for analysis.

#### Attributes:

&#x20;    **columns : Optional\[List\[str]]**

#### Methods:

&#x20;    **generate\_metrics(data:** [**InputData**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.metrics#evidently.metrics.base_metric.InputData)**, columns:** [**DatasetColumns**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.utils#evidently.utils.data_operations.DatasetColumns)**)**

## metric\_preset module <a href="#module-evidently.metric_preset.metric_preset" id="module-evidently.metric_preset.metric_preset"></a>

### class MetricPreset()

Bases: `object`

Base class for metric presets

#### Methods:

&#x20;    **abstract generate\_metrics(data:** [**InputData**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.metrics#evidently.metrics.base_metric.InputData)**, columns:** [**DatasetColumns**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.utils#evidently.utils.data_operations.DatasetColumns)**)**

## regression\_performance module <a href="#module-evidently.metric_preset.regression_performance" id="module-evidently.metric_preset.regression_performance"></a>

### class RegressionPreset(columns: Optional\[List\[str]] = None)

Bases: `MetricPreset`

Metric preset for Regression performance analysis.

Contains metrics:

* RegressionQualityMetric
* RegressionPredictedVsActualScatter
* RegressionPredictedVsActualPlot
* RegressionErrorPlot
* RegressionAbsPercentageErrorPlot
* RegressionErrorDistribution
* RegressionErrorNormality
* RegressionTopErrorMetric
* RegressionErrorBiasTable

#### Attributes:

&#x20;    **columns : Optional\[List\[str]]**

#### Methods:

&#x20;    **generate\_metrics(data:** [**InputData**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.metrics#evidently.metrics.base_metric.InputData)**, columns:** [**DatasetColumns**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.utils#evidently.utils.data_operations.DatasetColumns)**)**

## target\_drift module <a href="#module-evidently.metric_preset.target_drift" id="module-evidently.metric_preset.target_drift"></a>

### class TargetDriftPreset(columns: Optional\[List\[str]] = None, stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, cat\_stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, num\_stattest: Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]] = None, per\_column\_stattest: Optional\[Dict\[str, Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]], [StatTest](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)]]] = None, stattest\_threshold: Optional\[float] = None, cat\_stattest\_threshold: Optional\[float] = None, num\_stattest\_threshold: Optional\[float] = None, per\_column\_stattest\_threshold: Optional\[Dict\[str, float]] = None)

Bases: `MetricPreset`

Metric preset for Target Drift analysis.

Contains metrics:

* ColumnDriftMetric - for target and prediction if present in datasets.
* ColumnValuePlot - if task is regression.
* ColumnCorrelationsMetric - for target and prediction if present in datasets.
* TargetByFeaturesTable

#### Attributes:

&#x20;    **cat\_stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

&#x20;    **cat\_stattest\_threshold : Optional\[float]**

&#x20;    **columns : Optional\[List\[str]]**

&#x20;    **num\_stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

&#x20;    **num\_stattest\_threshold : Optional\[float]**

&#x20;    **per\_column\_stattest : Optional\[Dict\[str, Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]]**

&#x20;    **per\_column\_stattest\_threshold : Optional\[Dict\[str, float]]**

&#x20;    **stattest : Optional\[Union\[str, Callable\[\[Series, Series, str, float], Tuple\[float, bool]],** [**StatTest**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.calculations/evidently.calculations.stattests#evidently.calculations.stattests.registry.StatTest)**]]**

&#x20;    **stattest\_threshold : Optional\[float]**

#### Methods:

&#x20;    **generate\_metrics(data:** [**InputData**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.metrics#evidently.metrics.base_metric.InputData)**, columns:** [**DatasetColumns**](https://francesco.gitbook.io/docs.evidentlyai.com/reference/evidently.utils#evidently.utils.data_operations.DatasetColumns)**)**