Kaggle Facebook Recruiting Contest

THE DATA

• Data set: 7 million + stack overflow posts with tags

• Training set: 2 million stack overflow posts without tags

• Goal: supply tags for training set stack overflow posts

ATTACK 1

• Build Baysian classifiers for each tag in training set

• 1) tried applying entire posts to each classifier– Classifiers became too large and slow

• 2) Apply POS tagger to posts and only use nouns to train classifiers– Classifiers became too large and slow

ATTACK 2

• Text search of training set posts for list of high frequency training set tags

• 1) Simple application caused too many false positives

• 2) Finally rated each tag in list based on false positive to positive ration and removed problematic tags from list

284/367 - hoorah