Basic concepts for predicting

The basic concepts and vocabulary conventions for predicting are:

• Assisted labeling. Performing the prediction operation on unlabeled dataset entries and labeling results with a very high score as the ground truth. This is also known as active learning.
• Inference. An alternative and equivalent term for prediction.
• ONNX. An is an open-source format (Open Neural Network Exchange) that lets you create, train, and save a machine learning model. You can import such a model and incorporate it into your Aurora Imaging Library application for prediction.
• Predict engine. The processing device (for example, the CPU or GPU) on which prediction is performed.
• Score. An output of a classifier that determines how likely a target belongs to each class.
• Target. The image or set of features that the prediction operation classifies.