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Which of the following image data augmentation techniques allows a data scientist to increase the size of a data set?
Correct Answer: B
# Cropping involves selecting portions of an image to create multiple training samples from one image. This technique helps increase dataset size and variability, which improves model generalization. Why the other options are incorrect: * A: Clipping typically refers to limiting pixel values, not augmentation. * C: Masking hides or removes parts of an image - used more in object detection or inpainting, not to expand the dataset. * D: Scaling changes the image size but doesn't create new samples. Official References: * CompTIA DataX (DY0-001) Study Guide - Section 6.3:"Cropping is a data augmentation strategy that allows for synthetic expansion of the dataset by generating multiple views." -
