Methods and workflows for identifying unusual observations without assuming that rarity implies error or operational importance.
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Anomaly detection is not "find the weird rows." It is a decision about what counts as normal, made before you ever run an algorithm. Get that decision…
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Two detectors, one dataset, two different alert lists — and no labels to referee the disagreement.
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You fit an Isolation Forest, call decision_function, and get a column of numbers. You sort them, pick a cutoff, and ship the alerts. But if someone asks…
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A point can sit closer to its neighbors than anything else in the dataset and still be the anomaly. That is the contradiction Local Outlier Factor was…
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