Unsupervised Learning for Lexicon-Based Classification

21 Nov 2016 Jacob Eisenstein

In lexicon-based classification, documents are assigned labels by comparing the number of words that appear from two opposed lexicons, such as positive and negative sentiment. Creating such words lists is often easier than labeling instances, and they can be debugged by non-experts if classification performance is unsatisfactory... (read more)

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