Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.
| # | Year / Semester | Institute | Department | Course / Remark | Lecturer |
|---|---|---|---|---|---|
| 1. | 2023 - Year Term 1 | Full Time | CDS | CDS3004 - Data Mining | Prof. Wong Man Leung |
| 2. | 2022 - Second Semester | - | Computing & Decision Science | CDS3004 - Data Mining | Prof. Wong Man Leung |
| 3. | 2021 | - | Computing & Decision Science | CDS3004 - Data Mining | Prof. Wong Man Leung |
1 Introduction
2 Data
3 Classification: Basic Concepts and Techniques
4 Association Analysis: Basic Concepts and Algorithms
5 Cluster Analysis: Basic Concepts and Algorithms
6 Classification: Alternative Techniques
7 Association Analysis: Advanced Concepts
8 Cluster Analysis: Additional Issues and Algorithms
9 Anomaly Detection
10 Avoiding False Discoveries
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