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Many common text classifiers are linear classifiers
Support vector machines (with linear kernel)
Linear regression with threshold
Despite this similarity, noticeable performance differences
For separable problems, there is an infinite number of separating hyperplanes. Which one do you choose?
What to do for non-separable problems?
Different training methods pick different hyperplanes
Classifiers more powerful than linear often don’t perform better on text problems. Why?
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