You could use it to classify documents as "positive" or "negative", thus doing sentiment analysis. You could do it with financial news text, and classify documents as "stock went up" or "stock went down" after the release, and make (short-term) predictions of future stock movements. You can also see which words are important discriminants. Once you've trained a learning algorithm, you can use it on unseen data.
- The nearest neighbor learning algorithm
- The naive bayes learning algorithm
Here is part 6
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