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I need to design an algorithm such that it handles the request for shift swapping and recommends a list of people who are more likely to swap that shift with the person by analyzing previous data. Can anyone list the techniques that will help me to do this or a good starting point? I was thinking about training a Naive Bayes Classifier and using Mahaut for generating recommendation.

Paras
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This depends mostly on the amount of data you have about previous swaps. If all info you have is shift swap requests and yes/no answers to them per person, I doubt you can do much better than Naive Bayes.

To choose an effective classifier based on your data, see this stackoverflow post.

Furthermore, do you mean Mahout? Mahaut Doesn't give a lot of Machine Learning related entries.

Sijmen
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