title: Algorithm to cluster / assign observed values
body: <p>I am looking for an algorithm to solve the following problem:</p>
  
  <p>I have <code>n</code>client communicating values with a server. The values are basically an array of x probabilities (values between 0 and 1), e.g. <code>0, 0.5, 1, 0.7, 0.1,</code>. Every client communicates around 1000 of such arrays to the server. Over time, for each client these values change uniquely for each client.</p>
  
  <p>I want to take on the role of an observer, watching the traffic between client and server, capturing each communicated message, but without the knowledge who of the clients is the sender of the message. However, I know that these message change uniquely over time. So if I capture sufficient message, I will be able to distuingish between the clients.</p>
  
  <p>My question is now, what class of algorithms/approaches are suitable to perform such a "categorization" or "identification" to assign a captured message to a certain client on the basis of previous captures messages.</p>
  
  <p>I guess I will have to emply statistic. Do know of algorithms or approaches that could deal with this problem?</p>
  
  <p>Thanks</p>
  
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