Lecture01 - Data Mining: Principles and Algorithms Jianyong...

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2009/10/9 Data Mining: Principles and Algorithms 1 Data Mining: Principles and Algorithms Jianyong Wang Database Laboratory Department of Computer Science and Technology Tsinghua University, Beijing 100084 jianyong@tsinghua.edu.cn Course Website: http://dbgroup.cs.tsinghua.edu.cn/wangjy/DM/DataMining.html
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2009/10/9 Data Mining: Principles and Algorithms 2 Course Coverage Introduction Data Preprocessing Association and Correlation Analysis, and Pattern Discovery Classification and Prediction Cluster Analysis Advanced Topics (Optional) Conclusions and Future works
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2009/10/9 Data Mining: Principles and Algorithms 3 Text Books - J. Han and M. Kamber. Data Mining: Concepts and Techniques . Morgan Kaufmann, 2 nd ed., 2006 - P-N. Tan, M. Steinbach and V. Kumar, Introduction to Data Mining ,Wiley, 2005. Other reference books - S. Chakrabarti. Mining the Web: Statistical Analysis of Hypertex and Semi-Structured Data . Morgan Kaufmann, 2002 - T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction , Springer-Verlag, 2001 - T. M. Mitchell, Machine Learning , McGraw Hill, 1997 - I. H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations , Morgan Kaufmann, 2 nd ed. 2005 Text Book & Reference Books
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2009/10/9 Data Mining: Principles and Algorithms 4 Overall course evaluation - Course project: 40% » Expectation: Be familiar with decision tree-based classification for uncertain data. - One 90-minutes final examination: 60% » Open book, in-class (tentatively, the 16 th week) ˗ More details can be found from the course evaluation Website: » http://dbgroup.cs.tsinghua.edu.cn/wangjy/DM/CourseEvaluation.htm ˗ Teaching Assitant » Chuancong Gao, e-mail: chuancong@gmail.com Course Evaluation
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2009/10/9 Data Mining: Principles and Algorithms 5 Some slides used in this class are heavily borrowed from some publicly available lectures on data mining, and the following are some examples: - Lectures taught in Fudan Univ. in summer 2008 by Prof. Jiawei Han from UIUC - Lectures taught in Michigan State University by Prof. Pang- Ning Tan The copyright of these borrowed/revised slides still belongs to the original authors, and here we thank them for making their slides publicly available! Copyright Claim
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2009/10/9 Data Mining: Principles and Algorithms 6 Chapter 1. Introduction What ? - The definition of data mining Why? - The motivation of data mining How? - On what kind of data? - Data mining functionality - Major issues in data mining Major data mining research topics
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2009/10/9 Data Mining: Principles and Algorithms 7 What?
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2009/10/9 Data Mining: Principles and Algorithms 8 What is data mining - Extraction of interesting (non-trivial, implicit , previously unknown and potentially useful ) patterns or knowledge from huge amount of data - Alternative names » Knowledge discovery (mining) in databases (KDD) , data/pattern analysis,
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Lecture01 - Data Mining: Principles and Algorithms Jianyong...

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