Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
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 • Knowledge Processed data or information that conveys understanding or learning applicable to a problem or activity Interdisciplinary nature of data mining machine statistics learning (AI) DM databases Data Mining: A KDD Process Pattern Evaluation Data Mining Task-relevant Data Data Warehouse Selection Data Cleaning Data Integration 5 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. 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