Analyzing Articles on Hacker News Using NLP

Re:Analyzing Articles on Hacker News Using NLP by baccheion on Wednesday August 01, 2018 @01:37AM (#17659970)

I did one some years ago (basic attempt using XGBoost) and AUC was high 0.6s or low 0.7s.

I think I treated the title as a string rather than words and each column/feature was one letter. That is, if there were 256 possible characters and each title could only be 80 characters long, there'd be 256 * 80 * 2 columns (title + title reversed).

[ Parent | on HN ]

Re:Analyzing Articles on Hacker News Using NLP by minimaxir on Wednesday August 01, 2018 @01:57AM (#17660053)

If you are doing a classification model, what’s the score threshold?

The trick with that approach is if you set the threshold high, it’s very easy to get a model with a high accuracy since classes will be imbalanced. (The vast, vast majority of HN submissions do not do well)

[ Parent | on HN ]

Re:Analyzing Articles on Hacker News Using NLP by baccheion on Wednesday August 01, 2018 @02:25AM (#17660151)

If I remember correctly, HN's data dump included a made_front_page flag (not exact name). Also, XGBoost includes a feature that attempts to normalize against imbalanced classes. As for thresholds, there's only including submissions with at least average +/- standard_deviation votes.

[ Parent | on HN ]