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I have a sequence of actions dataset. There are 10 different actions, but lets say for simplicity that I have a1 and a2 actions. The data are not stationary. For some time we have one distribution of actions sequences probabilities and then another. RBM can model a distribution of stationary subsequences very well. However, I want to switch to new RBM as soon as distribution properties are changed. Also, I want to be able, after a training, to find a cluster(RBM id?) to what this sequence of actions applies. Is it realistic?

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