Share '10,000 observations and 100,000 parameters: what to do?'
Everybody learned in elementary statistical classes that when you have more parameters (in your statistical model) than observations, it is a recipe for disaster.
Here, I would like to provide two examples where more parameters than observations can successfully be handled:
Scoring system to detect fraud: logistic or linear regression: 500,000 binary rules (most of them with a triggering rate…
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