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I am a little worried about the accuracy of sentiment classifiers, relative to how often I see them used and in applied research settings. They work well for bi
by groceryheist 8y ago
I am a little worried about the accuracy of sentiment classifiers, relative to how often I see them used and in applied research settings. They work well for binary classification on Tweets and IMDB reviews and not much else (I guess they do alright at 93% if you magically have a parse tree).
- Radim 8y agoIt's not just sentiment classification. Many of these NLP methods overfit to the minutiae of the particular SOTA data set and data type. Language identification, NER, POS tagging, parsing, tokenization… you name it. Solved in theory, trouble in practice. Using the algos on a concrete project, with a concrete "upstream" goal, is the only way to assess the gap between SOTA and your needs. Don't blindly trust these 90+% scores.