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How to Improve the Performance of Visual Anomaly Detection Models
Apply the best methods from academia to get the most out of practical applications The post How to Improve the Performance of Visual Anomaly Detection Models ap...
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A Practical Toolkit for Time Series Anomaly Detection, Using Python
Here's how to detect point anomalies within each series, and identify anomalous signals across the whole bank The post A Practical Toolkit for Time Series Anoma...
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The Machine Learning “Advent Calendar” Day 9: LOF in Excel
In this article, we explore LOF through three simple steps: distances and neighbors, reachability distances, and the final LOF score. Using tiny datasets, we se...
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The Machine Learning “Advent Calendar” Day 8: Isolation Forest in Excel
Isolation Forest may look technical, but its idea is simple: isolate points using random splits. If a point is isolated quickly, it is an anomaly; if it takes m...
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[Paper] Anomaly Detection with Adaptive and Aggressive Rejection for Contaminated Training Data
Handling contaminated data poses a critical challenge in anomaly detection, as traditional models assume training on purely normal data. Conventional methods mi...