# 'Minimum confidence' presentation slideshows

## Association Rule Discovery

Association Rule Discovery. Bamshad Mobasher DePaul University. Market Basket Analysis. Goal of MBA is to find associations (affinities) among groups of items occurring in a transactional database has roots in analysis of point-of-sale data, as in supermarkets

By tareq
(96 views)

## Tutorial 4

Tutorial 4. Association rule mining. Goal: Find all rules that satisfy the user-specified minimum support ( minsup ) and minimum confidence ( minconf ). Assume all data are categorical. No good algorithm for numeric data.

By hume
(82 views)

## Section 5

Section 5. Data Mining. Section Content. 5.1 Introduction 5.2 Knowledge Discovery 5.3 Association Rules 5.4 Sequential Patterns 5.5 Classification and Regression 5.6 Other Forms of Data Mining 5. 7 Applications of Data Mining. 5.1 Data Mining Introduction. Data mining:

By nusa
(142 views)

## Α. Νανόπουλος, Γ. Μανωλόπουλος: Εισαγωγή στην Εξόρυξη και τις Αποθήκες Δεδομένων

Α. Νανόπουλος & Γ. Μανωλόπουλος Εισαγωγή στην Εξόρυξη & τις Αποθήκες Δεδομένων Κεφάλαιο 8 : Κανόνες Συσχέτισης http://delab.csd.auth.gr/books/grBooks/grBooks.html. Α. Νανόπουλος, Γ. Μανωλόπουλος: Εισαγωγή στην Εξόρυξη και τις Αποθήκες Δεδομένων. 1. Associations.

By gefjun
(121 views)

## ACCTG 6910 Building Enterprise & Business Intelligence Systems (e.bis)

ACCTG 6910 Building Enterprise & Business Intelligence Systems (e.bis). Association Rule Mining. Olivia R. Liu Sheng, Ph.D. Emma Eccles Jones Presidential Chair of Business. Main Expectations. Knowledge pattern in focus Definitions and examples A basic method How to tune the method

By micol
(119 views)

## 『 Data Mining 』

『 Data Mining 』. Start. By Jung, hae-sun. Contents. Introduction Definition Data Mining Applications Data Mining Tasks 5. Overview of the System 6 . Data Mining Analysis 7. Application 8. Reference. 1. Introduction. Data mining is related to - Data warehousing

By maris
(310 views)

## Mining Association Rules between Sets of Items in Large Databases

Mining Association Rules between Sets of Items in Large Databases. presented by Zhuang Wang. Outline. Introduction Formal Model Apriori Algorithm Experiments Summary. Introduction. Association rule:

By albina
(160 views)

## Association Rules

Association Rules. Hawaii International Conference on System Sciences (HICSS-40) January 2007 David L. Olson Yanhong Li. Fuzzy Association Rules. Association rules mining provides information to assess significant correlations in large databases IF X THEN Y Initial data mining analysis

By brandon-baird
(110 views)

## Association Rules

Association Rules. Olson Yanhong Li. Fuzzy Association Rules. Association rules mining provides information to assess significant correlations in large databases IF X THEN Y SUPPORT: degree to which relationship appears in data CONFIDENCE: probability that if X , then Y.

By clark-benjamin
(185 views)

## Market Basket Analysis and Association Rules

Market Basket Analysis and Association Rules. Chapter 14. Customers Tend to Buy Things Together …. Market Basket Analysis (MBA)?. Relationships through associations. Examples of association rules: {Bread}  {Milk} {Diaper}  {?} {Milk, Bread}  {?}.

(9 views)

## Association Rules

Association Rules. Olson Yanhong Li. Fuzzy Association Rules. Association rules mining provides information to assess significant correlations in large databases IF X THEN Y SUPPORT: degree to which relationship appears in data CONFIDENCE: probability that if X , then Y.

By sherrya
(1 views)

## Association Rules

Association Rules. Hawaii International Conference on System Sciences (HICSS-40) January 2007 David L. Olson Yanhong Li. Fuzzy Association Rules. Association rules mining provides information to assess significant correlations in large databases IF X THEN Y Initial data mining analysis

By wallsa
(1 views)

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