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For some classification needs. I have multivariate time series data composed from 4 stelite images in form of (145521 pixels, 4 dates, 2 bands) I made a classification with tempCNN to classify the data into 5 classes. However there is a big gap between the class 1,2 with 500 samples and 4,5 with 1452485 samples.

I' am wondering if there is a method that help me oversamling the two first classes to make my dataset more adequate for classification.

ala
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  • Class imbalance almost certainly is not a problem, and there is no need to solve a non-problem. https://stats.stackexchange.com/questions/357466/are-unbalanced-datasets-problematic-and-how-does-oversampling-purport-to-he https://www.fharrell.com/post/class-damage/ https://www.fharrell.com/post/classification/ https://stats.stackexchange.com/a/359936/247274 https://stats.stackexchange.com/questions/464636/proper-scoring-rule-when-there-is-a-decision-to-make-e-g-spam-vs-ham-email https://twitter.com/f2harrell/status/1062424969366462473?lang=en – Dave Oct 08 '21 at 23:09
  • Hi, thank you for your response. According to what you have mentionned class imbalance can be a problem according to its use. In my case I am classifying land use classes. and the gap between the classes samples have given an erroned classification map – ala Oct 09 '21 at 16:52
  • I encourage you to read the material I linked. – Dave Oct 09 '21 at 19:15

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