1

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
  • 11
  • 2

1 Answers1

2

actually there is a lib in python for that "imbalanced-learn" (although u can do it manually) .

you can check the docs it's very easy to use

sbabti zied
  • 784
  • 5
  • 17
  • 1
    thank you very much, However i am afraid that it is not suitable for time series processing – ala Oct 08 '21 at 20:43
  • in this case i suggest you do it manually ( i mean create an algorithm with some conditions , arrays and for loops to accomplish this task). – sbabti zied Oct 08 '21 at 20:57