Hello Steven,
I've asked this question too:
http://mail-archives.apache.org/mod_mbox/mahout-user/201105.mbox/%3cbanlktinyohrcynt0xzrpoqqg3zkepvk...@mail.gmail.com%3E
unfortunately, Mahout's Naive Bayes implemention can't calculate
probabilities. You are now probably really astonished - I could'nt
believe it too, as I read that (I think this is some kind of 'strange',
since Bayes's main concept is probability calculation). It's a pitty,
that such a great framework like Mahout has restricted the Bayesian
concept that way. In addition, Naive Bayes is (as far as I know) only
text-oriented, you can apply it only on documents . Mahout is still
wonderful, though, because it lets us calculate probabilities using
Logistic Regression.
That's why I switched to using Mahout's Logistic Regression
implementation: using OnlineLogisticRegression.java#classifyScalar()
returns a probability. Logistic Regression has also the advantage, that
it can handle continous values directly, while in Bayes' Clasifier you
should categorize data first.
You can try the class TrainLogisticTest.java from the mahout-examples in
order to see how it works. See also the calculation of probability in
TrainLogistic.java:
double p = lr.classifyScalar(input);
Am 15.06.2011 16:51, schrieb Steven Raemaekers:
Hello,
Currently I'm working on a classifier to classify documents written in
different programming languages in the correct category. I made a test and a
training set, and I get a confusion table as a result. This is nice, but the
program does not supply any probabilities/uncertainties that a particular file
belongs to a certain category, it only returns whether or not a single file
belongs to a category or not. Because it is a Bayesian algorithm, probabilities
must be involved somehow.
What I would like to have is for a single input file the chance/probability of
that file belonging to each category, for instance like this:
C: 25%
C++: 50%
Java: 25%
The classifyDocument method in the class BayesAlgorithm does return numbers,
but these are not really probabilities since they do not add up to 1.
Looking in the javadoc it says that these numbers are dot products between the
vector of this document and the training set.
So my question is, is it possible to convert the numbers as stored in
ClassifierResult and calculated in BayesAlgorithm.classifyDocument to some kind
of probability?
Regards,
Steven
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