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Statistical classification is the problem of identifying the sub-population to which new observations belong, where the identity of the sub-population is unknown, on the basis of a training set of data containing observations whose sub-population is known. Therefore these classifications will show a variable behavior which can be studied by statistics.

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How to use weights for each observation in a classifier

Resample the dataset: You can sample important observations more often which is very easy to implement without changing your classification model. …
Aray Karjauv's user avatar
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Best way to make an image classification model with dynamic image sizes

The solutions you suggest are valid except for the last one. Since you are using 2d CNN you cannot use 1d input. In fact, your model already has a Rescaling preprocessing layer that will normalize the …
Aray Karjauv's user avatar