Timeline for Text-Classification-Problem: Is Word2Vec/NN the best approach?
Current License: CC BY-SA 3.0
4 events
| when toggle format | what | by | license | comment | |
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| Nov 5, 2015 at 19:58 | comment | added | rushimg | I would use the Doc2Vec model due to the fact that it removes the bag-of-words assumption of the max-ent model. If tf-idf is used as features in the max-ent model then this would also reduce the impact of common words. I think trying out both methods and tweaking them would be the best course of action. | |
| Nov 5, 2015 at 6:02 | comment | added | Shankar | Thanks @rushimg. If the categories are closely related, i.e. the para of text that are used as input have a large amount of common words, which of the two approaches would be better at understanding the context and differentiating between the two? | |
| Nov 4, 2015 at 16:49 | review | First posts | |||
| Nov 5, 2015 at 4:24 | |||||
| Nov 4, 2015 at 16:45 | history | answered | rushimg | CC BY-SA 3.0 |