Part 3 Part 3 – Local Outlier Factor scores & Conclusion In Part 2, I demonstrated how to compute the local reachability density for each data point. The local reachability density grants us insight as to how “isolated” a data point is. In this third and final blog post, I will compare each point’s local […]
PART 2 Part 2 – Reachability-Distance & Local Reachability Density In Part 1, I motivated the need for a density-based approach to outlier detection, and then I talked you through the first step of using the K-Distance as a framework for quantifying how “distant” a data point is from its neighbors. Today, I will walk […]
User Behavior Analytics Finding Anomalous Users through the Local Outlier Factor Algorithm Part 1 – Motivation and K-Distance How do you identify users who are behaving anomalously? One way to tackle this problem is to define a set of rules that all user activity should conform to. If a user’s behavior breaks one or several […]
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