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Which domain does this problem belong to?

Given a set of products some are classified as cheap and some not. The task is to determine the price range (probabilistic) for cheap products. Supervised classifiers arrive at a function and can classify a new instance but does not provide the range of feature values. This seems like a pattern recognition problem but I am not able to get which class of problems it belongs to.

There might be hundreds of features of the products (price being one of them) and the ask is to identify a profile of products (the range of values for various features) which are mostly classified as cheap. Could this be a rule mining problem?

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  • $\begingroup$ like how to find a pattern saying, all products with price <2000 are generally classified as cheap for 90% of the cases. This would be the output after learning over 100s of product features (say for example). $\endgroup$ – user439521 Nov 22 '14 at 18:58
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    $\begingroup$ This doesn't look like a machine learning problem; it looks like a charting problem. $\endgroup$ – Kyle Jones Nov 23 '14 at 1:07
  • $\begingroup$ Could you describe your problem with more details. I assume there are other characteristics than prices associated with the products, and other classifications. $\endgroup$ – babou Nov 23 '14 at 16:50
  • $\begingroup$ @babou made the edit. $\endgroup$ – user439521 Nov 23 '14 at 17:43
  • $\begingroup$ Is it the case that you have both the price and the cheap/expensive information for each product? I suppose you can then make a global classification using all features including price to decide whether something is cheap of expensive. There should be standard techniques for that. An given a product and all its caracteristic, you can then assess what price range can be considered cheap. $\endgroup$ – babou Nov 23 '14 at 18:04

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