I am currently working on the task of eCommerce product name classification, so I have categories and subcategories in product data. I noticed that using subcategories as labels delivers worse results (84% acc) than categories (94% acc). But subcategories are more precise as labels, what's important for the whole task. And then I got an idea to first do category classification and then based on the results continue with subcategories within the predicted category.

The problem here is that I do not know how to approach this problem/define network architecture. Any hints on the neural networks, how to deal with it?

Currently I defined network like this:

model = Sequential()
model.add(Dense(400, input_shape=(FEATURE_NUM,)))
  • $\begingroup$ Did you manage to solve this question somehow? $\endgroup$ – Franco Piccolo Jun 24 '20 at 11:25
  • $\begingroup$ Unfortunately, not yet. $\endgroup$ – chacid Jun 25 '20 at 12:08

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