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It represents an intuitively slightly ridiculous null hypothesis that often works surprisingly well as a feature, most likely because it correlates with a lot of other features of interest. Examples: (to be inserted) |
A feature-effective test that's caught my eye
Wang, Zhao and Aron Culotta, When do Words Matter? Understanding the Impact of Lexical Choice on Audience Perception using Individual Treatment Effect Estimation. AAAI 2019. [code]
How do we proceed during the age of deep learning, where, for prediction, we don't need to (aren't supposed to) worry about features anymore?
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