传统电脑决策.pptx

The Application of Fuzzy Sets on Data Mining
Prof. Tzung-Pei Hong
Department of Electrical Engineering National University of Kaohsiung
Outline
Introduction
Review
Data Mining
Fuzzy Sets
Fuzzy Data Mining
Fuzzy Association Rules (I)
Fuzzy Association Rules (II)
Fuzzy Generalized Association Rules
Fuzzy Web Mining
Outline
Review of GA
Fuzzy data mining for membership
functions and rules
Two approaches
Conclusion
Reasons for data mining
Sam
Goods
Supermarket
How to arrange goods into supermarket?
Reasons for data mining
Sam
customer
how to make the marketing strategies for these customer?
Mining association rules
Bread
Milk
IF bread is bought then milk is bought
The role of data mining
Useful patterns
Transaction data
Preprocess data
Data Mining
Knowledge and strategy
Data
information
Different kinds of knowledge
Association rules
Generalized association rules
Sequential patterns
Quantitative association rules
Classification rules
Clustering rules
etc…
Focus
Apriori Algorithm
Proposed by Agrawal et al.
Step1:Define minsup and minconf
ex: minsup=50%
minconf=50%
Step2:Find large itemsets
Step3:Generate association rules
Example
Large itemsets
Scan
Database
Scan
Database
Scan
Database
Itemset
Sup.
{A}
2
{B}
3
{C}
3
{E}
3
L
1