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Micro and Macro Averages for imbalance multiclass classification
A macro-average will compute the metric independently for each class and then take the average hence treating all classes equally, whereas a micro-average will aggregate the contributions of all classes to compute the average metric.
Explain Pooling layers: Max Pooling, Average Pooling, Global Average Pooling, and Global Max pooling.
Global Average Pooling does something different. It applies average pooling on the spatial dimensions until each spatial dimension is one, and leaves other dimensions unchanged.
How to use class weight in CrossEntropyLoss for an imbalanced dataset?
how to create a loss function for an imbalanced dataset in which minority class proportionally to its underrepresentation. You will use PyTorch to define the loss function and class weights to help the model learn from the imbalanced data.