Im new to ML. I'm trying to predict if a new Music Album will exceed X amount of dollars in Sales. I'm looking to build a model to go only after potential best sellers. I do have historic data for Music Sales from 2010 till 2016. I have many signals:

  • Music Genre
  • Music Band/Artist name
  • Label
  • Year released
  • Country of origin
  • Part of a Series/Volume... etc.
  • Sales per month

What type of ML problem is this one?

  • $\begingroup$ Please give your question a better title - half the questions on here could have that title. $\endgroup$ – Spacedman Feb 7 '17 at 8:10

There are two broad classes of problems in machine learning, classification and regression. As in this answer, Regression involves estimating or predicting a response (the dependent variable is continuous). Classification is identifying group membership (the dependent variable is discrete).

Your problem is a regression problem, you must try to estimate the real number of sales. You can look here for a similar problem and techniques to solve it.

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  • $\begingroup$ As I add more and more variables, is this a Linear regression problem? $\endgroup$ – gogasca Feb 8 '17 at 2:26
  • 1
    $\begingroup$ In a linear regression problem, the dependence between the variables is linear. If you add more variables this doesn't mean the dependence becomes linear, however you could add a set of variables that have a linear relation with the dependent variable. You should look at en.wikipedia.org/wiki/Feature_engineering for a discussion of how to deal with variables (features) $\endgroup$ – Dani Mesejo Feb 8 '17 at 15:59

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