From the course: Machine Learning and AI Foundations: Clustering and Association

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Using SOM for anomaly detection

Using SOM for anomaly detection

From the course: Machine Learning and AI Foundations: Clustering and Association

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Using SOM for anomaly detection

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- [Instructor] We're going to pick up where we left off in the same stream. We're going to do things a little bit differently this time because what we're about to try is a lot of fun, but it's computationally intensive. What we're going to do is we're going to run a self-organizing map on this data set, which as you recall, has a half million records. If you want to go ahead and run this on your own you certainly can. The self organizing maps node is called Kohonen in Modeler, and you can hook this up and the one modification that I've made under expert is that I'm going to request a 10 by 10 map. However, on my machine it took about 45 minutes to run on the half million records. So what I've done for each of these three demonstrations, I have saved the end state of the stream in the exercise files for that video. And what I'm actually going to do is open that end state stream now so that we can look at the completed version after the 45 minutes. So where I've placed this particular…

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