In SAS DLPy, a data scientist trains an image classifier and wants to augment the training data to improve generalization. Which DLPy class is used to specify image augmentation transformations?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — c is correct because in SAS DLPy, image data augmentation is configured through the ImageTable (or CASTable) loading process, where augmentation parameters such as random flipping, rotation, and cropping are specified as arguments to the data loading or fitting functions. The model.fit() method accepts augmentation configurations through its data handling pipeline.
Full explanation below image
Full Explanation
C is correct because in SAS DLPy, image data augmentation is configured through the ImageTable (or CASTable) loading process, where augmentation parameters such as random flipping, rotation, and cropping are specified as arguments to the data loading or fitting functions. The model.fit() method accepts augmentation configurations through its data handling pipeline. A and B describe class names that do not exist in standard SAS DLPy. D is wrong because PROC HPNEURAL does not support image augmentation.