August 2015
Beginner to intermediate
294 pages
5h 20m
English
Content preview from Mastering Python for Data Science
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The naive Bayes classifier
The naive Bayes classifier is a simple probabilistic classifier, which is based on the Bayes theorem. The assumption made is that there is strong interdependence between the features, because of which it is called naive. The following is the Bayes theorem:
Here in the preceding formula, A and B are events, P(A) and P(B) are the probabilities of A and B and are interdependent of each other. P(A|B) is the probability of A, given that B is True, which is a conditional probability. P(B|A) is the probability of B, given that A is True. The naive Bayes formula is as follows:
Let's try solving this equation to understand the naive ...
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I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.