This week I presented 'Stack Exchange Tagger', a student research article that focused on predicting tags using a classifier, which was part of a more general problem of developing accurate classifiers for large scale text datasets. The students took 10,000 questions from StackOverflow and analyzed the text using a Linear Support Vector Classification. The results showed that the linear SVC performed better than all other kernel functions, and the best accuracy obtained from the analysis was 54.75%. The students were able to conclude that the result of the accuracy could have been better if user information had been considered.
Next week, I will be developing the abstract of our project and we will be closer to submitting to OCWIC, 2017.
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