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Oracle Data Mining Ying Zhang

Oracle Data Mining Ying Zhang. Agenda. Data Mining Data Mining Algorithms Oracle DM Demo. 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

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Oracle Data Mining Ying Zhang

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  1. OracleData 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. Interdisciplinarynature of data mining machine statistics learning (AI) DM databases

  5. Data Mining: A KDD Process Knowledge Pattern Evaluation Data Mining Task-relevant Data Selection DataWarehouse DataCleaning Data Integration

  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

  13. Q & A

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