RGPV / RGTU M.Tech. Sofware Engineering 2nd sem Data Mining Syllabus

Tags: Data Mining Syllabus, M.Tech Syllabus, Sofware Engineering M.Tech Syllabus, Data Mining Syllabus, M.Tech 2nd sem Syllabus, Sofware Engineering M.Tech 2nd semester Syllabus

Rajiv Gandhi Technological University, Bhopal (MP)
M.Tech. Sofware Engineering
Data Mining Syllabus
Enforced From Session 2009-10 SECOND SEMESTER (PROPOSED)

UNIT-1: Introduction of Data Mining, Data, Information and Knowledge Discovery, Data Mining Functionalities, Data Mining System categorization and its Issues. Data Processing: - Data Cleaning, Data Integration and Transformation. Data Reduction, Data Mining Statistics. Guidelines for Successful Data Mining, Data Mining Software.

UNIT-2: Classification:-Introduction, Decision Tree, Algorithms for Decision Tree Induction, Characteristics of Decision Tree Induction, Evaluation the Performance of a Classifier:-Holdout Method, Random Sub sampling, Cross-Validation. Rule Based Classifier, Nearest –Neighbors Classifiers, Bayesian Classifiers, Support Vector Machine (SVM)

UNIT-3: Cluster Analysis:- Introduction, Desired Features of Cluster Analysis, Cluster Evaluation, Agglomerative Hierarchical Clustering, Prototype-Based Clustering, Density-Based Clustering, Graph based Clustering, Scalable Clustering Algorithms

UNIT-4: Association Rule Mining:-Introduction, Basic, The Task and a Naïve Algorithm, Apriori Algorithms, Improving the efficiency of the Apriori Algorithm, Apriori-Tid, Direct Hasing and Pruning(DHP),Dynamic Itemset Counting (DIC), Mining Frequent Patterns without Candidate Generation(FP-Growth),Performance Evaluation of Algorithms, Software for Association Rule Mining

UNIT-5: Spatial Data Mining, Multimedia Data Mining, Text Ming, Web Data Mining.

1. Jiawei Han and Micheline Kamber, Data Mining Concepts & Techniques, Elsevier Pub.
2. Tan,Steinbach,Kumar, Introduction To Data Mining,Pearson Education.
3. Arun.K.Pujari, Data Mining Techniques.
4. N.P Gopalan: Data Mining Technique & Trend, PHI
5. Ali: Data Mining:Methods and Techniques, Cenage Learning
6. Hand, Mannila & Smith: Principle of Data Mining, PHI
7. Vikram Pudi: Data Mining, Oxford Univ Press

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