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Prior probability and Naive Bayes
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Topic: Prior probability and Naive Bayes (Read 772 times)
patty
Newbie
Posts: 1
Prior probability and Naive Bayes
«
on:
June 18, 2013, 03:54:49 AM »
Hi all,
Thank you for taking the time to read this question! Is it possible to create a Naive Bayes classifier from the prior probabilities? I do not have a training set per se, and I was hoping to not include the correct outcome in the data. So, I was hoping to predict the outcome from the prior probabilities, not from a training set. Can this be done in RapidMiner?
On a related note, is it possible to include the prior probabilities of the outcomes? If, for example, I know that 80% of the outcomes will be of one type and the remaining 20% will be the other, is it possible to enter this into the program?
Thank you,
Patty
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Marius
Administrator
Hero Member
Posts: 1753
Re: Prior probability and Naive Bayes
«
Reply #1 on:
June 20, 2013, 12:23:49 PM »
What you want is probably not possible. RapidMiner usually needs training data to create any kind of model. Maybe you can create a rule-based process with the Branch operator or the Generate Attributes operator, but that will be a bit tedious.
Best regards,
Marius
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