April 2016
Beginner to intermediate
384 pages
8h 36m
English
Content preview from Practical Data Analysis CookbookBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Classifying with Naïve Bayes
The Naïve Bayes classifier is one of the simplest classification techniques. It uses Bayes' Theorem of conditional probability of an event happening given that some other event occurs. The Naïve Bayes classifier leverages the very familiar formula:
P(A|B) = P(B|A) P(A) / P(B)
In other words, we want to calculate the probability of the outbound call resulting in a credit application (A) given the various characteristics of the call and caller (B). This is equivalent to the ratio of the product of the observed frequency of applying for credit: the P(A), and the frequency of such characteristics of the call and caller occurring for those who had taken the offer in the past: the P(B|A), to the frequency of such a call ...
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