data mining overview. lecture objectives after this lecture, you should be able to: 1.explain key...

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Data Mining Overview

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Page 1: Data Mining Overview. Lecture Objectives After this lecture, you should be able to: 1.Explain key data mining tasks in your own words. 2.Draw an overview

Data Mining

Overview

Page 2: Data Mining Overview. Lecture Objectives After this lecture, you should be able to: 1.Explain key data mining tasks in your own words. 2.Draw an overview

Lecture Objectives

After this lecture, you should be able to:

1. Explain key data mining tasks in your own words.

2. Draw an overview of the Data Mining Process.

3. Discuss one broad business application of data mining.

4. Explain one way to evaluate effectiveness of a Data Mining project.

Page 3: Data Mining Overview. Lecture Objectives After this lecture, you should be able to: 1.Explain key data mining tasks in your own words. 2.Draw an overview

Data Mining Tasks

1. Prediction / Classification

2. Segmentation

3. Association

Page 4: Data Mining Overview. Lecture Objectives After this lecture, you should be able to: 1.Explain key data mining tasks in your own words. 2.Draw an overview

Course Overview/Techniques UsedData PreparationPrediction/Classification

Discriminant AnalysisLogistic RegressionArtificial Neural NetworksClassification Trees (CART, CHAID)

SegmentationJudgementFactor AnalysisCluster Analysis

AssociationMarket Basket AnalysisOther Correlation Based techniques

Page 5: Data Mining Overview. Lecture Objectives After this lecture, you should be able to: 1.Explain key data mining tasks in your own words. 2.Draw an overview

Data Mining ProcessSource: CRISP-DM (SPSS.com website)

Page 6: Data Mining Overview. Lecture Objectives After this lecture, you should be able to: 1.Explain key data mining tasks in your own words. 2.Draw an overview

Application in Financial Services

Product Planning

Customer Acquisitio

n

Collections

and Recovery

Customer Manage-

ment

Customer Valuation

Stage 1 Stage 2

Stage 4

Stage 3

Page 7: Data Mining Overview. Lecture Objectives After this lecture, you should be able to: 1.Explain key data mining tasks in your own words. 2.Draw an overview

Measuring Effectiveness: Lift/Gains Chart

Dr. Satish Nargundkar

Percent of population targeted

Perc

en

t of

pote

nti

al

resp

on

ders

cap

ture

d

100

1000

90

45

45

Targeting

Random mailing

Page 8: Data Mining Overview. Lecture Objectives After this lecture, you should be able to: 1.Explain key data mining tasks in your own words. 2.Draw an overview

Discussion

1. Can you think of other applications?2. What are some limitations of Data Mining?3. What are future possibilities?