If I have a training dataset that has 1083 samples and a testing dataset that has 79871 samples, how do I go about making the samples equal? I have been using S
I am trying to understand where exactly SMOTE-ing should occur when training a model with cross-validation. I understand that all pre-processing steps should oc
While doing the SMOTE , i get the following error. "Error in matrix(if (is.null(value)) logical() else value, nrow = nr, dimnames = list(rn, : length of 'di
I am working with Orange 3.30.1 trying to use the Python Script widget to add SMOTE to my data classification problem (the Orange team has refrained from implem
I'm trying to implement SMOTENC inside a column transformer. However I'm getting error. The code and the error is provided below. #Create a mask for categorical