January 2011
Intermediate to advanced
420 pages
12h 32m
English
Content preview from Practical Applications of Data Mining
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190 Chapter 5 rough SetS and BayeS’ theorieS
5.4 APPLICATIONS BASED ON BAYES’ AND ROUGH SETS
5.4.1 Customer Tendency Analysis Using
Bayes’ Theory
Consider a store manager who wants to derive a purchase pattern of coffee
and sugar buyers. He wants to find out how likely a person buying coffee
will also buy sugar. The store manager knows that generally 50% of people
buying sugar also buy coffee. The prior probability of a customer buying
sugar is 1/200 and prior probability of a customer buying coffee is 1/50.
Therefore, we can obtain the following by using Bayes’ theorem:
PCoffeeSugar
PCoffee
(|)%.
()/
==
=
50 05
150
PPSugar Coffee
PCoffeeSug