How to extract a model from Robust PCA
jacobcybulski
New Altair Community Member
In general, Robust PCA (rPCA) is an excellent algorithm capable of doing both PCA in the presence of outliers and identifying two classes of outliers, i.e. those that fall within the subset of principal components and those outside (which otherwise would not be detected after dimensionality reduction). Anomaly Detection extension offers rPCA, which implements the algorithm but it hides the PCA model. Is there a way of extracting the PCA model from rPCA? Or should rPCA be moved to the RM core with full features? (of course it is possible to do this in R or a hack in Python)
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Best Answer
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Hi @jacobcybulski ,as far as I know this is not possible. One would need to dig into the source code of rPCA in the extension to figure this one out.Cheers,Martin5
Altair EmployeeAnswers
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Hi @jacobcybulski ,as far as I know this is not possible. One would need to dig into the source code of rPCA in the extension to figure this one out.Cheers,Martin5
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I just checked the code available on github: https://github.com/Markus-Go/rapidminer-anomalydetection/blob/master/src/de/dfki/madm/anomalydetection/operator/statistical_based/RobustPCAOperator.javaIt seems to be, that it has a model internally, which can be exported with not too crazy effort.
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@mschmitz , yes I have just been staring at it, it seems the code uses two PCAs, one is robust.
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