arovinel
Hi there,I'm creating clusters from a network, and while performing multiple clustering, I come across the option "Use Multinet". What does this option do? Does it connect separate Factor networks file to the "Final" output one?ThanksAndrea
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Dan
Hi Andrea,The original clustering algorithm used in BayesiaLab is based on a Naive structure (the latent variable that represents the segmentation is the parent of all the variables used for clustering) and the Expectation-Maximization algorithm. The Naive structure thus implies the conditional independency of the clustering variables given the latent variable. The Multinet algorithm is a new algorithm for relaxing this conditional independency hypothesis. Instead of using a Naive structure, the algorithm uses an Augmented Naive structure, in which the intra-cluster conditional dependencies between the children are represented. Each cluster thus represents instances that not only "look similar" (Naive) but also "behave similarly" (Augmented Naive).
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arovinel
Hi Dan, thanks a lot for the quick reply!This is an important feature for me, as I'm working with variables that cannot be considered independent when clustering, and Augmented Naive BN solve this problem. Another quick question, can I still export only factors when using this option? I'm asking this because exporting only factors I can use any learning algorithm to construct a PSE, instead of being limited to Taboo.Thanks!
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Dan
This new algorithm is an option in the Clustering tool. You thus have the same features as the original algorithm.
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