Oracle Data Mining Ying Zhang

OracleData 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 • Knowledge Processed data or information that conveys understanding or learning applicable to a problem or activity

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

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

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

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

The Data Mining Process

Generalization vs. Overfitting

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

Oracle Data Mining Example Use Cases

Oracle 11g Data Mining algorithm

Oracle Data Mining Ying Zhang

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