I find the java documentation for the classifyfull method in Naive Bayes

I have instantiated a Naive Bayes classifier

StandardNaiveBayesClassifier classifier = new
StandardNaiveBayesClassifier(model);

and then I try to evaluate a particular vector

Vector resultVector = classifier.classifyFull(v);

I have 30 classes so I get a 30 dimensional vector whose entries are the
following

[-306.4584092661414, -334.36171437440134, -316.25155747226177,
-333.67996893153475, -315.6780180023944, -313.4109704147129,
-311.7022222825663, -406.6561643676268, -329.5159468330492,
-313.770853095979, -324.7031385545635, -309.1217427600103,
-335.4600698447981, -319.9293126441192, -316.93276118648254,
-395.1045866311986, -335.58699112395, -317.9441037627677,
-296.7236735135832, -335.03832449410646, -300.1938445981156,
-334.8021989394156, -317.114625495575, -316.74878644634754,
-311.25148771061464, -259.207734355347, -310.828983048158,
-307.28537172070793, -339.037232482962, -328.043473305476]


How am I supposed to interpret these entries?  I would like to be able to
say if a classifier classifies a vector with 90% confidence then I will use
that category or else I will leave it uncategorized.  Are there ways I can
get such information from these vectors?

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