問題タブ [imblearn]

Currently, I'm working on my first Convolutional Neural Network for a project in university. I have to create a model that can recognize if a cable has a defect by only using images of "good" and "defect" cables in Google Colab.

My dataset is unbalanced; I have more images of 'good' cables then 'defect' ones. That's why I used the imblearn-library and its function 'balanced_batch_generator' so that I could oversample the minority class. To work with the generator, I needed to reshape my X from dim 4 in dim 2. Now when I want to run the balanced batches in my model, I get an error due to the 2x2 shape and I don't know how to reshape the batches inside of the generator to get the model running.

I also tried to put a 'Flatten'-layer as the first layer with typed in input_shape to change the dense layer from the batch_generator but then I can't compile/build the model because it expects more dimensions than I can put in.

Here is my code:

Error message:

Can anybody help me? Or give me a hint?

GridSearchCV を使用して DecisionTreeClassifiers のハイパーパラメーターを設定しようとしていますが、データのバランスが取れていないため、imblearn.over_sampling.RandomOverSampler を使用しようとしています。

これはエラーを返します:

ここで何が間違っていますか？

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