Page History: Data Mining (Fall, 2012)

Compare Page Revisions

120 119 118 117 116 115 114 113 112 111 110 109 108 107 106 105 104 103 102 101 100 99 98 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 69 68 67 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50 49 48 47 46 45 44 43 42 41 40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 Current 120 119 118 117 116 115 114 113 112 111 110 109 108 107 106 105 104 103 102 101 100 99 98 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 69 68 67 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50 49 48 47 46 45 44 43 42 41 40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0

« Older Revision - Back to Page History - Newer Revision »

Page Revision: 2012/09/27 14:19

(Back to homepage)

Information

• Course Number: 081202B3
• To: M. Sc. students of Department of Computer Science and Technology, Nanjing University.
• Classroom: 221, Computer Science and Technology Building, Xianlin Campus
• Time: 16:00 -- 17:50, Wednesday
• Office Hour: 14:30 - 15:30, Wednesday (Rm 917)
• Text Book: D. Hand, H. Mannila, P. Smyth. Principles of Data Mining. MIT Press, MA:Cambridge, 2001.
• Main Reference Books:
  • J. Han, M. Kamber. Data Mining: Concepts and Techniques, 2nd edition. Morgan Kaufmann Publishers, 2006
  • I. H. Witten, E. Frank. Data Mining: Practical Machine Learning Tools and Techniques, 3rd edition. Morgan Kaufmann Publishers, 2011
  • P.-N. Tan, M. Steinbach, V. Kumar. Introduction to Data Mining, Addison-Wesley, 2006.
  • E. Alpaydin. Introduction to Machine Learning, 2nd edition. MIT Press, 2010.
• Grading: Final exam (30%) + assignment 1 (20%) + assignment 2 (15%) + assignment 3 (15%) + assignment 4 (20%)
• TA: Mr. Teng Zhang and Mr. Chao Qian

Assignments

Assignment 1: Write a report on data mining applications         Due on Sept. 26, 2012         TA page

Assignment 2: A classification task         Due on Oct. 17, 2012         TA page

Assignment 3: A clustering task         Due on Nov. 7, 2012         TA page

Assignment 4: Mining from a real-world data set         Due on Dec. 5, 2012         TA page

Lecture slides

   

9/12: Introduction (Download PDF)		Reading material: Z.-H. Zhou. Three perspectives of data mining. Artificial Intelligence, 2003, 143(1): 139-146. H.-P. Kriegel, et al. Future trends in data mining. Data Mining and Knowledge Discovery, 2007, 15(1): 87-97. Q. Yang and X. Wu. 10 challenging problems in data mining research. International Journal of Information Technology & Decision Making, 2006, 5(4): 597-604.
9/19: Data, Measurements, and Visualization (Download PDF)		Reading material: M. C. F. de Oliveira and H. Levkowitz. From visual data exploration to visual data mining: A survey. IEEE TVCG, 2003, 9(3): 378-394. H. Liu, F. Hussain, C. L. Tan, and M. Dash. Discretization: An enabling technique. DMKD, 2002, 6(4): 393-423. J. Dougherty, R. Kohavi, M. Sahami. Supervised and unsupervised discretization of continuous features. In Proceedings of ICML'95, 194-202, Tahoe City, CA. X. Zhu and X. Wu. Class noise vs. attribute noise: A qualitative study of their impacts. AI Review, 2004, 22(3-4): 177-210. Link: A javascript for simple data visualization
9/26: Supervised Learning (Download PDF)		Reading material: Chapter 2 of Introduction to Machine Learning (E. Alpaydin, MIT Press, 2010). L. Valiant. A theory of the learnable. Communication of the ACM, 27(11):1134-1142, 1984.
10/10: Decision Tree, Neural Networks, and Linear Models
10/17: Discussion of Assignment 1
10/31: Parametric Methods, Lazy Methods, and Hasing
11/7: Ensemble Methods
11/14: Clustering
11/21: Handing Big Data
11/28: Experiment Design and Analysis / Discussion of Assignment 2
12/5: Feature Extraction

Links

• Weka An open source (Java) machine learning/data mining algorithms software.

• R Project An open source platform for statistic computing using R script language.
  • Machine learning packages for R

• ACM SIGKDD The website of the ACM Special Interest Group on Knowledge Discovery and Data Mining.
  • ACM SIGKDD Explorations Newsletters A magazine of SIGKDD.

• KDnuggets A website for data mining resources.

Major academic venues

• Journals in data mining: DMKD, TKDD, TKDE, KAIS
• Journals in machine learning: MLJ, JMLR
• Journals in database: TODS, VLDBJ
• Journals in information retrieval: TOIS, IP&M, IRJ
• Journals in web search and mining: WWWJ, TOIT, TWeb
• Conferences in data mining: KDD, ICDM, SDM, ECML/PKDD, PAKDD
• Conferences in machine learning: ICML, NIPS, COLT
• Conferences in database: SIGMOD, VLDB, ICDE
• Conferences in information retrieval: SIGIR, CIKM
• Conferences in web search and mining: WWW, WSDM

The end