> ## Documentation Index
> Fetch the complete documentation index at: https://docs.abbyy.com/llms.txt
> Use this file to discover all available pages before exploring further.

# ValidationResult Object (IValidationResult Interface)

This object contains the detailed result of checking the model's performance.

## Properties

| Name              | Type                                                                                                                                                                                                                                  | Description                                                                                 |
| ----------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------- |
| Accuracy          | [double](/fine-reader/engine/guided-tour/advanced-techniques/programming-aspects/working-with-properties), read-only                                                                                                                  | Returns the average accuracy of all the models on all training iterations.                  |
| ConfusionMatrix   | [ConfusionMatrix](/fine-reader/engine/api-reference/classification-related-objects/confusionmatrix), [read-only](/fine-reader/engine/guided-tour/advanced-techniques/programming-aspects/working-with-properties#readonly_properties) | Returns the confusion matrix for the classification model.                                  |
| FMeasure          | [double](/fine-reader/engine/guided-tour/advanced-techniques/programming-aspects/working-with-properties), read-only                                                                                                                  | Returns the F-measure, or F1 score, of the classification model.                            |
| Precision         | [double](/fine-reader/engine/guided-tour/advanced-techniques/programming-aspects/working-with-properties), read-only                                                                                                                  | Returns the precision (positive predictive value) of the classification model.              |
| Recall            | [double](/fine-reader/engine/guided-tour/advanced-techniques/programming-aspects/working-with-properties), read-only                                                                                                                  | Returns the recall, or sensitivity, of the classification model.                            |
| StandardDeviation | [double](/fine-reader/engine/guided-tour/advanced-techniques/programming-aspects/working-with-properties), read-only                                                                                                                  | Returns the standard deviation of the model accuracy calculated on each training iteration. |

## Related objects

<img src="https://mintcdn.com/abbyy/B_SRGbkkbQ9YH40E/images/fine-reader/engine/validationresult.gif?s=d2658029dc855022b76c4005501f7965" alt="ValidationResult" width="216" height="148" data-path="images/fine-reader/engine/validationresult.gif" />[](/fine-reader/engine/api-reference/classification-related-objects/confusionmatrix#axislabels)[](/fine-reader/engine/api-reference/classification-related-objects/trainingresult#validationresult)[](/fine-reader/engine/api-reference/classification-related-objects/trainingresult)[](/fine-reader/engine/api-reference/classification-related-objects/confusionmatrix)[](/fine-reader/engine/api-reference/supplementary-objects-and-methods/stringscollection)[](/fine-reader/engine/api-reference/classification-related-objects/trainingresults)

[Object Diagram](/fine-reader/engine/api-reference/object-diagram)

## Samples

This object is used in the [Classification](/fine-reader/engine/guided-tour/samples#classification) demo tool in Windows and the [Classification](/fine-reader/engine/guided-tour/samples#classification_unix) code sample in Linux and macOS.