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Demystifying PyTorch’s WeightedRandomSampler by example
Aug. 30, 2022, 2:41 p.m. | Chris Hughes
Towards Data Science - Medium towardsdatascience.com
A straightforward approach to dealing with imbalanced datasets
Recently, I found myself in the familiar situation of working with a vastly unbalanced dataset, which was impacting the training of my CNN model on a computer vision task. Whilst there are various ways of approaching this, the findings of a study into handling class imbalance when training CNN models on different datasets concluded that, in almost all cases, the best strategy was oversampling the minority class(es); increasing the frequency that images …
computer vision deep-dives deep learning example imbalanced-data pytorch
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