Chapter 1 Data Mining in Context
What is Data Mining
Data mining is the process of exploration and analysis, by automatic or semiautomatic means, of large quantities of data in order to discover meaningful pattern and rules.–John Wiley
What Can Data Mining DO?
Classification
examine the features of a newly presented object and assign to it a predefined class
Estimation
deal with continuously valued outcome
Prediction
Prediction cannot be checked about accuracy. We can only wait and see
Affinity Grouping
things go together (cross-selling opportunities)
Clustering
diverse group into similar subgroups
Description and Visualization
data visualization
The Business Context for Data Mining
- large quantities of data
- worth learning
Research Tool
Process Improvement
Marketing
Customer Relationship Management
The Technical Context for Data Mining
- Algorithms
- Data
- Modeling practices
Machine Learning
Neural network
Decision Trees
Statistics
Decision Support
Data Warehouse
OLAP
Decision Support Fusion
Computer Technology
The Societal Context for Data Mining
Chapter 2 Why Master the Art?
Four Approaches to Data Mining
Purchasing Scores
Purchasing Software
Purchasing Models
neural net models for predicting fraud in credit, product Falcon. Concern-false positive-innocent people
vertical application
Purchasing Model-Building Software
Quadstone Decision house
what tools can and cannot automate
assumption is important
Hiring Outside Experts
- one time vs on-going
- source of data
- how be employed
- availability and skill level
Lessons Learned
- understand business problem
- select relevant data
- transform data
- interpret result