1. Oracle Data Mining Ying Zhang

2. Agenda Data Mining Data Mining Algorithms Oracle DM Demo

3. Data, Information, Knowledge Data Items that are the most elementary descriptions of things, events, activities, and transactions Information Organized data that has meaning and value Knowledge Processed data or information that conveys understanding or learning applicable to a problem or activity

4. Interdisciplinary nature of data mining m achine statistics learning (AI) DM databases

5. 5 Data Cleaning Data Integration Data Warehouse Task-relevant Data Selection Data Mining Pattern Evaluation Data Mining: A KDD Process

6. Data Mining Algorithms Decision Trees Nearest Neighbor Classification Neural Networks Rule Induction K-means Clustering

7. The Two Concept Learning Paradigms Supervised Learning –builds a learner model using data instances of known origin. – and uses the model to determine the outcome new instances of unknown origin. –Classification, Regression Unsupervised Learning – A data mining method that builds models from data without predefined classes. –Clustering, Associate Rules, Feature Extraction

8. The Data Mining Process

9. Generalization vs. Overfitting

10. Oracle Data Mining Popular models in classification, clustering, regression, association, feature extraction etc. Statistics SQL & Java Data Miner

11. Oracle Data Mining Example Use Cases

12. Oracle 11g Data Mining algorithm

19. Q & A