05-15-2025, 08:22 AM
And, according to logic, it makes sense to train the second layer to work with the data of the first layer ONLY WHEN the data of the first layer is correct.
I guess it's this assumption that is not right for normal ANN training. It is a holistic process where all nodes in all layers are treated equally and all are updated for each step by back propagation.
You can't update the first layer without taking account of what the next layer will do. Why have more than 1 layer otherwise.
I suggest you continue with your strategy, but realise it is conceptually different to classical ANN training.
I guess it's this assumption that is not right for normal ANN training. It is a holistic process where all nodes in all layers are treated equally and all are updated for each step by back propagation.
You can't update the first layer without taking account of what the next layer will do. Why have more than 1 layer otherwise.
I suggest you continue with your strategy, but realise it is conceptually different to classical ANN training.