I am using CNN for Sentence Classification code by Yoonkim. This is used for text classification. I noticed that he uses softmax layer and negative log likelihood error. This is optimal for single label multiclass classification. I now have a dataset which is for multilabel-multiclass classification. What are the ideal activation methods and error functions to use? I felt that, using softmax layer will give the sum of probabilities as 1 but in this case since it belongs to different labels, at each instance we might have high probability for each class. So I believe that Softmax is not an ideal option. Am I right?I find data for images but nothing prominent for text. Can anyone refer me to some source?
Activation method and Loss function for multilabel multiclass classification
nlp;deep learning;multiclass classification;multilabel classification;loss function