# Statistical Concepts

In order to understand the statistics output by the VisionPro Deep Learning tools, it is important to understand concepts related to labels, markings, and testing and training image set splits, and how they interact with the metrics used by VisionPro Deep Learning tools.

- Labels are the user-generated input data that establish the ground truth for the tool. Ground truth refers to the undisputed facts about the images in your application, for example what you, as the human determine to be the key information within the image (feature, character, defect, class). Labels establish the ground truth, which is used for both training and performance analysis. So it is imperative that you label accurately. For more information, refer to the Labeling topics.
- Markings are the VisionPro Deep Learning-generated outputs which are used to graphically display the neural network model's interpretation, along with generating the statistical results. For more information, refer to the Markings topics.
- The Testing/Training image set splits refer to the portion of labeled images that are used for training and testing. By default, VisionPro Deep Learning uses a 50% testing/training split in the Training Set dialog. However, this can be modified, based on the application needs. For more information, refer to the Image Sample Sets topics.