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Lecture Notes 1: Introduction to Data Mining Zhangxi Lin ISQS 6347 Texas Tech University ISQS 6347, Data & Text Mining
What is Data Mining? ,[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
Data Mining Process ISQS 6347, Data & Text Mining
What is Text Mining? ,[object Object],ISQS 6347, Data & Text Mining Patterns Trends Associations
Motivation for Text Mining ,[object Object],[object Object],ISQS 6347, Data & Text Mining 90% Structured Numerical or Coded Information 10% Unstructured or Semi-structured Information
Text Mining Process ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Why Mine Data? Commercial Viewpoint ISQS 6347, Data & Text Mining
Why Mine Data? Scientific Viewpoint ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],Origins of Data Mining ISQS 6347, Data & Text Mining Machine Learning/ Pattern Recognition Statistics/ AI Data Mining Database systems
ISQS 6347, Data & Text Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining Tasks ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
Classification: Definition ,[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
Classification Example ISQS 6347, Data & Text Mining categorical categorical continuous class Training Set Learn Classifier Test Set Model
Classification: Application 1 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining From [Berry & Linoff] Data Mining Techniques, 1997
Classification: Application 2 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
Clustering Definition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
Illustrating Clustering ISQS 6347, Data & Text Mining ,[object Object],Intracluster distances are minimized Intercluster distances are maximized
Clustering Example ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
Association Rule Discovery: Definition ,[object Object],[object Object],ISQS 6347, Data & Text Mining Rules Discovered: {Milk} --> {Coke} {Diaper, Milk} --> {Beer}
Association Rule Discovery Example ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
Regression ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
Deviation/Anomaly Detection ,[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining Typical network traffic at University level may reach over 100 million connections per day
Text Mining Tasks ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Example: Decision Support using Bank Call Center Data ISQS 6347, Data & Text Mining
Example: Decision Support using Bank Call Center Data ,[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining AC2G31, 01, 0101, PCC, 021, 0053352, NEW YORK, NY , H-SUPRVR8, STMT , “ Mr. Stark has been with the company for about 20 yrs. He hates his stmt format and wishes that we would show a daily balance to help him know when he falls below the required balance on the account.”
Challenges of Data Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
Challenges of Text Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining
SAS Training/Self-taught Courses ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ISQS 6347, Data & Text Mining

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  • 1. Lecture Notes 1: Introduction to Data Mining Zhangxi Lin ISQS 6347 Texas Tech University ISQS 6347, Data & Text Mining
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  • 3. Data Mining Process ISQS 6347, Data & Text Mining
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  • 13. Classification Example ISQS 6347, Data & Text Mining categorical categorical continuous class Training Set Learn Classifier Test Set Model
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