S = 5, A = 56, B = 43 and C = 2
Monday, July 18, 2011
Friday, April 29, 2011
CAT - 3 Syllabus
Other Mining techniques: Web Mining [Introduction, Web Mining, Web Content Mining, Web Structure, Web Usage Mining], Temporal and Spatial Data Mining [Introduction, What is Temporal Data Mining,Spatial Mining and Spatial Mining Tasks] 4Hrs
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Predictive Methods: Surveying Predictive Modeling Techniques, Current Techniques have the Power, Mathematical basics, Polynomial Regression Models, Machine Learning and Predictive Models, Decision Values and Decision Surfaces, Complex Decision Surfaces. 4 Hrs.
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Data Mining: Case Study/Tools: Data Mining in Insurance, Data Mining in Health Care and Medicine, Data Mining in Government.
Wednesday, April 13, 2011
Monday, April 11, 2011
CAT - 2 Syllabus
- Clustering Techniques: Clustering Paradigms, Partitioning Algorithm, k-Medoid Algorithm, CLARA, CLARANS, Hierarchical Clustering, DBSCAN, BIRCH, CURE, Categorical Clustering Algorithms, STIRR, ROCK, CACTUS etc. 6 Hrs.
- Decision Trees: What is Decision trees?, Tree Construction, Splitting Criteria, Decision Tree Construction Algorithms, CART, ID3, C4.5, CHAID, Decision tree Construction with Presorting, Rainforest, Approximate methods, CLOUDS, BOAT, Pruning Technique, Integration, an Ideal Algorithm etc. 4 Hrs
3. Data Mining Techniques and Algorithms: FP-tree Growth Algorithm, Discussion, Incremental Algorithm, Border Algorithm.
Wednesday, March 30, 2011
Saturday, March 19, 2011
Thursday, March 17, 2011
Syllabus for CAT - 1 | 18th March
1)Introduction and Basic Concepts: What is Data Mining? Definition, Comparison of Database Management System and Data Mining, Motivation, Knowledge Discovery Vs Data Mining, Classifications, Context, Mining Problems, Challenges, Applications of Data Mining, Benefits of Data Mining, Data Mining process. 10 Hrs.
2)Knowledge Discovery: What is Knowledge Discovery, Knowledge in Discovery, Data for Data Mining, Data Resources, Meta Data, Data Representation, Data Quality, Features, Sampling, Data Summarization, Missing Data, and Incorrect Values. 6 Hrs.
3)Data Mining Techniques and Algorithms: Association Rules: What is an Association rule, Methods, A Priori Algorithm, Partition Algorithm, Pincer-Search Algorithm, Dynamic Item set Counting Algorithm, FP-tree Growth Algorithm, Discussion, Incremental Algorithm, Border Algorithm, Generalized Association Rule, Constraints
[Portions which are marked in red are not for CAT - 1]
Saturday, February 26, 2011
Sunday, February 20, 2011
Friday, February 4, 2011
Daily Attendance Sheet
Dear All, This is my new experiment in giving you the flexibility in attending the classes. Further to my various means of delivering the course content through blog like Notes via Goolge Docs/ Presentations, SMS Alerts, Google groups, Text Book PDF along with regular class room sessions, this semester for my Data Mining subject, your physical presence in the class room is required only once in the week, that is on saturday (taking into account your current time table for A and B divs).
Tuesday, February 1, 2011
Monday, January 31, 2011
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