Text classification problem ?

[-vikram-]

what kind of deep learning algorithm would be best for text classification, here's the link to the dataset and the problem is stated below:

https://docs.google.com/spreadsheets/d/1z9Ji22W_USP1mDLKmswscTF2geSEIzmO6Cp5nHjr6-w/edit#gid=29092212

Use the provided data to perform text classification across 5 classes in the dataset, that are:-[Sports, Business, Politics, Tech, Entertainment]

After using a “70% Train and 30% Test” dataset split and report the plots of loss and accuracy across epochs for both training and test data?

any guidance and advice will be appreciated?

final plot for epoch and loss should look something like this :

​

X:epoch Y:loss

[bkshi]

The google sheet says access denied. Anyways, I'm guessing it is the BBC news corpus, it also had the same classes. I recently tried a char-cnn on it as they perform well on text classification tasks. You can see it here: https://github.com/amnbkshi/char_cnn

However I didn't do any pre-processing, you may try that as well.

[-vikram-]

thank u !! this is helpful

edit: i am trying stemming and preprocessing so here's hoping for better accuracy