https://ask.ghassem.com/tag/cluster Powered by Question2Answer https://ask.ghassem.com/1000/which-algorithm-best-detect-anomalies-within-login-events I am trying to build an unsupervised ML model to detect anomalies within 5000+ users&#039; login data. &nbsp;I selected 5 features contained within each of the user-login events (e.g. IP, hour of day, day of week, device_id, OS). &nbsp;I am looking for the best algorithm to use. &nbsp;I am considering using density function to determine probabilities of the feature values and whether an event is an outlier. &nbsp;The problem is that feature values are only relevant to the specific user. &nbsp;For example, you cannot compare login IP across users, login IP is only applicable to the user. <br /> Ultimately, I want to detect events that are changes in a user login behavior, like different IP, day, hour, device_id, or OS, where the more features that have changed increase the probability of an outlier. <br /> At this point, I am not sure how to build a model with data that contains multiple users, because I don&#039;t know how to separate the user data so the model is trained per user and finding anomalies within the individual user&#039;s features.<br /> <br /> I also don&#039;t have any labeled data to use for testing, should I fabricate some?<br /> <br /> Any advice greatly appreciated.<br /> <br /> Thank you! Machine Learning https://ask.ghassem.com/1000/which-algorithm-best-detect-anomalies-within-login-events Tue, 05 Oct 2021 17:45:38 +0000