A Visual Understanding of Bias and Variance

A guide to develop deeper intuitions for these two concepts

Bias and variance are two of the most fundamental terms when it comes to statistical modeling, and as such machine learning as well. However, understanding of bias and variance in the machine learning community are somewhat fuzzy, in part because many existing articles on the subject try to produce shorthand analogies (“bias” = “underfit”, “variance” = “overfit”, the bullseye diagrams). While these analogies are …

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