> ## 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.

# Classifier statistics

> Evaluate classifier statistics in FlexiLayout Studio: true and false positives, precision, recall, F-measure, plus confusion matrix and per-class reports.

After training is complete, the classification results are used to form a statistics report.

## Classification trigger types

* If the class assigned to a page corresponds to a reference class, this is classified as a True Positive (TP) trigger.
* If no class was assigned to a page with no reference class, this is classified as a True Negative (TN) trigger.
* If the class assigned to a page does not correspond to a reference class, this is classified as a False Positive (FP) trigger.
* If no class was assigned to a page that has a reference class, this is classified as a False Negative (FN) trigger.

As such, a tally is formed for each class, documenting the number of times it was:

* Correctly assigned (TP)
* Correctly not assigned (TN)
* Incorrectly assigned (FP)
* Incorrectly not assigned (FN)

## View the statistics

To view the statistics, select **Classifier** > **Show statistics**.

## Precision, recall, and F-measure

The higher the precision, recall, and the F-measure, the better the classification results are. For more information about how the F-measure is calculated, see the [Glossary](/flexi-capture/appendix/glossary-main-body). The F-measure is a balanced measurement of both precision and recall and allows for a cumulative evaluation of the classification quality using these parameters. For more information about increasing the F-measure, see [Tips for improving classification quality](/flexi-capture/fls/classify-fls-better-work).

## Additional statistics tabs

For quality evaluation purposes, further statistics are also available in the following tabs.

| Tab                     | Description                                                                                                                                                                                                                                                                                                                                                              |
| ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **Confusion Matrix**    | A visual representation of which documents are most often confused by a classifier. The cells in the diagonal of the matrix show how many of the documents were classified correctly. The right column and the last row contain information about documents that were not assigned any class. The rest of the cells show the documents that were incorrectly classified. |
| **Confusing Classes**   | A list of classes that were mixed up by the classifier. This statistic can help you figure out which classes are most often confused with each other.                                                                                                                                                                                                                    |
| **Statistics by Class** | Detailed statistics for each class. Lets you identify the classes that cause the classifier to make the most mistakes.                                                                                                                                                                                                                                                   |