multi-class-text-classification-cnn-rnn
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jiegzhan
How to deal with the imbalance data problem?
I tried to transplant the code on my own text classification data( 47 classes in 42000 records), finding out that the classifier would tend to choose the larger classes like THEFT, ASSULT and so forth. How you guys deal with the imbalance data to make them seems more 'balance'?
I've tried to replace the loss function, from Cross Entropy to Weighted Cross Entropy, to give the smaller groups more weights. It works out fairly but the accuracy got only around 70%...