# Precision, Recall, and F-Score for Blue Read

The Blue Read tool interprets Recall, Precision and F-Score as follows:

- Precision

  Precision is the percentage of detected features that are not in the training set and that correctly match the labeled features. For example, a Precision score of 90% for character “A” means that the neural network correctly identifies "A" against all other character features with a 90% chance given the test data.

  Labeled Image | Precision Results

- Recall

  Recall is the percentage of labeled features that are not in the training set and that are correctly identified by the tool. For example, a Recall score of 90% for character “A” means that the neural network catches 90% of all appearances of " an “A" among the test data.

  Labeled Image | Recall Results

- F-Score

  F-Score is the harmonic average between the Precision and Recall scores.​​

  Note:

  If possible, the use of a model may help filter out spurious matches. When using a model, a low Precision score can be less problematic.

  No model | Model in use