This power point presentation gives a brief introduction to data mining

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2. DATA MINING - BASICS
Dr. V. Subha, B.E., M.E., Ph.D.,
Assistant Professor,
Department of Computer Science & Engineering,
Manonmaniam Sundaranar University,
Tirunelveli.
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3. CONTENTS
1. Introduction to Data Mining
2. Data Mining techniques
3. Data Mining Resources
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4. 1. INTRODUCTION TO DATA MINING
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5. Definition of data mining
• Process of identifying valid, novel,
potentially useful, and ultimately
understandable patterns in data.
- Predicts outcomes of future
observations.
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6. Confluence of different disciplines
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7. Steps in Data Mining Evolution
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8. Data Mining - Motivation
• Growth in data.
• High dimensionality of data.
• Heterogeneous and complex data.
• Development of commercial data mining software.
• Growth of computing power and storage capacity.
• Limitation of humans.
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9. Why Data Mining ?
• Credit ratings :
• Given a database of 100,000 names, which persons are the least likely
to default on their credit cards?
• Fraud detection :
• Which types of transactions are likely to be fraudulent, given the
demographics and transactional history of a particular customer?
• Customer relationship management:
• Which of my customers are likely to be the most loyal, and which are
most likely to leave for a competitor?
Data Mining helps extract such information
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10. Types of data analysis
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11. Knowledge Discovery in Databases (KDD)
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12. Steps of KDD Process
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13. Applications of data mining
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14. 2. DATA MINING TECHNIQUES
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15. Data Mining Techniques
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16. Data Mining Techniques…
• Unsupervised learning
- No knowledge of output
- Self-guided learning algorithm.
• Supervised learning
- Knowledge of output
- Learning with an expert/teacher
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17. Data Mining Techniques…
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18. 3. DATA MINING - RESOURCES
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19. Data mining Tools - Open Source
DataMelt
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20. Data mining Tools - Proprietary License
Oracle Data Mining
IBM Cognos IBM SPSS Modeler
SAS Data Mining Sisense
SSDT
Teradata Board toolkit Dundas BI
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