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Bounding Excess Generalization Error

I am sharing a new free video where I work through a great common argument that bounds expected excess generalization error as a ratio of model complexity (in rows) over training set size (again in rows), independent of problem dimension. (link) For more of my notes on support vector machines […]

Your Lopsided Model is Out to Get You

For classification problems I argue one of the biggest steps you can take to improve the quality and utility of your models is to prefer models that return scores or return probabilities instead of classification rules. Doing this also opens a second large opportunity for improvement: working with your domain […]