Feature/multi class support #50
Open
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
added 2 commits
November 28, 2016 15:17
- multi-classification - predefined training/cv data set - character-based embedding
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
I used this code for multi-class classification of short Japanese text (which worked quite well, btw. thanks!) I made the following enhancements.
MultiClassDataLoader)MultiClassDataLoader)CharDataProcessor)While making these changes, I kept the original implementation as
BinaryClassDataLoaderandWordDataProcessor. The code is backward compatible by using the combo.You can mix and swap the classes (
(Binary|Multi)ClassDataLoaderand(Word|Char)DataProcessor) intrain.pyandeval.pyAny combo works.I also added a new set of data files for multi-class classification as an example. They're just straight format conversion from the original RT data.