How to use ensemble learning to combine multiple trained pattern recognition neural networks?
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I saved the neural networks (patternnet) with seperate classes
for example:
Neural Network 1:
3-class problem
Neural Network 2:
Another 3 class problem
Neural Network 3:
Another 3 class problem
Is there any way to use ensemble learning to combine these neural networks to make an ensemble of say 9 classes.
can we pass input to the (combined) ensemble to classify the class or predict any one class from the 9 classes.
I am new to ensemble learning..
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Answers (1)
Varun Sai Alaparthi
on 21 Nov 2022
Hello Raja,
I don’t suggest ensembling these networks as they are trained for different classes. For example, Neural network 1 isn’t aware of the classes that Neural network 3 is trained on. So, it might affect the final performance of the ensembled model.
Ensembling would be effective if all the neural networks are trained for 9 classes.
The better alternative would be to retrain a single model for 9 classes or ensemble models trained for all 9 classes.
I hope this information helps and please reach out for any further issues.
2 Comments
Varun Sai Alaparthi
on 25 Nov 2022
Hello Raja,
Yes is it possible to combine neural networks using ensembling.There are different ensembling methods that you can leverage to combine multiple neural networks like stacking ,boosting etc. Please check which technique works best for your use case.
Please refer to this links for information on different ensembling techniques :
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