Given a set of historical data points, I am trying to predict a continuous output of which I have no historical record of, therefore the problem is of an unsupervised nature.

I am wondering if there is any method or approach I should take to tackle this problem? Essentially, how to build a model that will provide an output that is not clustered?

  • $\begingroup$ I would add details about your available data as well as the way you are planning to frame the problem(i.e unsupervised anomaly detection). $\endgroup$ – hisairnessag3 Jun 9 '19 at 11:46

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