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Comprehensive Data Mining Course Overview - ICS426

This detailed syllabus for ICS426 outlines the Data Mining course, based on the second edition of "Data Mining: Concepts and Techniques" by Jiawei Han and Micheline Kamber. Key components include attendance (2%), quizzes (12%), homework (6%), a project (12%), two major exams (38%), and a final exam (30%). The course covers essential topics such as data preprocessing, OLAP technology, mining associations, classification, and cluster analysis, with specific durations allocated for each chapter to enhance student understanding.

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Comprehensive Data Mining Course Overview - ICS426

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  1. Syllabus ICS426: The course

  2. - The course … • Book: • Title: Data Mining Concepts and Techniques • Authors: Jiawei and Micheline Kamber • Edition: Second • Grade Distribution • Attend.& participation 2% • 4 Quizzes: 12% • 2 Home works: 6% • A project 12% • Major 1: 18% • Major 2: 20% • Final: 30% ICS426: The course

  3. … - The course … • Ch 1: Introduction ( 0.5 week) • Ch 2: Data Preprocessing (2.5 weeks) • Ch 3: DW and OLAP Technology: An Introduction (2 weeks) • Ch 4: Advanced Data Cube Technology and Data Generalization (2.5) • Ch 5: Mining Frequent Patterns, Association and Correlations (2 weeks) • Ch 6: Classification and Prediction (3 weeks) • Ch 7: Cluster Analysis (2.5 weeks) ICS426: The course

  4. … - The course (4) DS OLAP (2) (3) DP DW DS DM (5) Association DS (6) Classification (7) Clustering DS = Data source DW = Data warehouse DM = Data Mining DP = Data processing ICS426: The course

  5. END ICS426: The course

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