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A probability provides a quantitative description of the likely occurrence of a particular event.
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Naive Bayes Classifier
= 100% / (100% + 0%) = 100%
Fishing (F) & Wedding (W)
P(both F & W/just F) = 2/3 = 67%
P( (total user either-both F & W)/total) = (3-2)/3 = 33%
Normalize Probability = 67% / (67% + 33%) = 67% … that based on the data, I'm calculating the posterior probability (normalized probability) correctly? …