Why does nobody talk about pinning down training data BEFORE you build the model?
A guy at the Austin meetup ripped my sentiment project apart and said my labels were mush, so I spent 3 weeks relabeling 4,000 samples and my accuracy went from 71% to 88%. How are you all handling data quality before you even touch a model?