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?