Hello, My question is the following:
i have an multiclass problem ( classes 1-5 prediction). If i split the data into classes 1,3,5 ( first dataset) and classes 2 and 4 (second dataset). I trained models with every dataset separately. I'm getting better results insteat of using all classes in one dataset and one model. But the problem is, i dont know which model i should choose at the beginning, cause i dont know if the input is in class 1,3,5 or 2,4. So in general: Trained model #1 with dataset containing classes 1,3 and 5 as targets. Trained model #2 with dataset containing class 2 and 4 as targets. Is there a way to combine these models?? so depending on the Input, he should choose model #1 ore model #2 . but i dont know how i should classifie them. Is there is a way with bayse or something like that? best regards, Herb
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