# Optimizing Green Classify Using Statistical Results

To optimize the Green Classify tool, consider the following:

- To avoid False Positives, target a Precision score of 100
- To avoid False Negatives, target a Recall score of 100

Otherwise, target the following:

- For unbalanced problems where sparse classes matter, go by the F-Score.
- Use the F-Score averaged over all classes.
- Set the Threshold parameter to 0% to avoid a varying rate of non-classified views.

Note: If you face an unexpected underperformance of results and suspect mislabeling or noisy labels as the cause of the underperformance, you can examine the quality level of the label for each view A view of an image is a region of pixels in an image. Tool processing is limited to the pixels within the view. You can manually specify a view, or you can use the results of an upstream tool to generate a view. and correct the wrong label.