Chap11_AssociationRules

Chap11_AssociationRules - Chapter 11 Association Rules Data...

Info iconThis preview shows pages 1–10. Sign up to view the full content.

View Full Document Right Arrow Icon
Chapter 11 – Association Rules © Galit Shmueli and Peter Bruce 2008 Data Mining for Business Intelligence Shmueli, Patel & Bruce
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
What are Association Rules? Study of “what goes with what” “Customers who bought X also bought Y” What symptoms go with what diagnosis Transaction-based or event-based Also called “market basket analysis” and “affinity analysis” Originated with study of customer transactions databases to determine associations among items purchased
Background image of page 2
Used in many recommender systems
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Generating Rules
Background image of page 4
Terms “IF” part = antecedent “THEN” part = consequent “Item set” = the items (e.g., products) comprising the antecedent or consequent Antecedent and consequent are disjoint (i.e., have no items in common)
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Tiny Example: Phone Faceplates
Background image of page 6
Many Rules are Possible For example: Transaction 1 supports several rules, such as “If red, then white” (“If a red faceplate is purchased, then so is a white one”) “If white, then red” “If red and white, then green” + several more
Background image of page 7

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Frequent Item Sets Ideally, we want to create all possible combinations of items Problem: computation time grows exponentially as # items increases Solution: consider only “frequent item sets” Criterion for frequent: support
Background image of page 8
Support Support = # (or percent) of transactions that include
Background image of page 9

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 10
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 11/09/2011 for the course MAR 08 taught by Professor Staff during the Spring '08 term at Youngstown State University.

Page1 / 21

Chap11_AssociationRules - Chapter 11 Association Rules Data...

This preview shows document pages 1 - 10. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online