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The problem I want to solve is as follows: I have data about how many teaching hours different students spend with their teacher in order to pass their exams. The teaching varies from 25-55 hours. In the school there are approximately 15 teachers and given a set of 10 student-teacher features that describe personality characteristics such as, age, sex, education, nationality, etc., I want to develop a student-teacher match model in order to minimize the teaching hours a student needs to pass the exams.

Any idea of what sort of algorithms I should use, or any examples I can look at?

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  • $\begingroup$ Maybe for Clarification. Do you envision this as a Classification or as a Minimization Problem: Do you want to find the ideal solution for the current data or do you want to be able to predict it for, lets say, future students? $\endgroup$ – El Burro Jul 1 '19 at 11:58
  • $\begingroup$ Thanks @ElBurro. I think it's a classification problem and yes I want to predict what is the best student-teacher match for incoming future students. $\endgroup$ – Chris Ng Jul 1 '19 at 12:02
  • $\begingroup$ Are there any boundary conditions (student/ teacher ratio- do you want to find the solution that is best for everyone together or rather the solution that is best for one student?) $\endgroup$ – El Burro Jul 1 '19 at 12:05
  • $\begingroup$ I'd like the system to recommend top 3-5 candidate teachers for a new, incoming student. No more conditions. The data I have is pairs of student/teachers and how many teaching hours needed for a specific student with a specific teacher to pass the exams $\endgroup$ – Chris Ng Jul 1 '19 at 12:44
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    $\begingroup$ How many students do you have in your existing dataset? $\endgroup$ – El Burro Jul 1 '19 at 13:14
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This seems to be a recommendation problem. You can find a nice overview here.

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  • $\begingroup$ Thanks @ElBurro $\endgroup$ – Chris Ng Jul 1 '19 at 14:08

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