# Is there a theory behind which model is good for a classification task for the convolutional neural network?

Let say I'm trying to apply CNN for image classification. There are lots of different models to choose and we can try an ensemble, but given a limit amount of resources, it does not allow to try everything.

Is there a theory behind which model is good for a classification task for the convolutional neural network?

Right now, I'm just taking an average of three predictions.

predictions_model = [y_pred_xceptionAug,y_pred_Dense121_Aug,y_pred_resnet50Aug]
predictions = np.mean(predictions_model,axis=0)


But each model's performance is different. Is there better way for ensemble methods?

• i cant tell if youre interestted in best way to get bang for buck using an ensemble or the theory of what CNN's would work best for you – mshlis Jul 30 at 1:45