Download Data Mining Methodologies

Data Mining Methodologies
Chapter 6
Why Should There be a Standard Process?
• The data mining process must be reliable and repeatable by people with
little data mining background.
• Framework for recording experience
 Allows projects to be replicated
• Aid to project planning and management
• Co fort fa tor for e adopters
 Demonstrates maturity of Data Mining
Data Mining Methodologies:
Different Perspectives
Data Mining Methodologies:
Business Perspective
• There is a big variety of data mining software and
methodologies in the market. Companies may use different
data mining methodologies.
• Although their basic tenets are the same, each sheds a slightly
different light on the process.
• Examples:
• ฀CRI“P_DM y “P““ Cle e ti e uses the 5 A’s
• ฀“A“’s “EMMA tool set a e used as a part of a y iterati e
data mining methodology adopted by the client.
“A“’s “EMMA Tool “et for
Data Mining Methodology
“A“’s “EMMA Tool “et for
Data Mining Methodology
•
“EMMA is ot a data i i g ethodology ut rather a
logical organization of the functional tool set of SAS Enterprise
Mi er for arryi g out the ore tasks of data i i g.
• Enterprise Miner can be used as part of any iterative data
mining methodology adopted by the client.
• SEMMA is focused on the model development aspects of data
mining, i.e. Sample; Explore; Modify; Model; & Assess.
SPSS CRISP-DM Methodology
Data Mining Methodology: 11 Steps
Data mining is all about creating models
Predictive & Descriptive
Data Mining Models
Lift