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Data Mining and Data Warehouse Description

Key Elements

Code

ILOG 544

Formation

M2 Software Engineering

Semester

1

Credits

3

Number of Teaching Hours

18

Number of Tutoring Sessions

0

Number of Laboratory Sessions

6

This course is optional

Content

Objective

Content

Introduction to Data Mining: Origins of Data Mining, Tasks Content: • Data : Types of Data , Quality , Data Preprocessing , Measures of Similarity and Dissimilarity • Exploring Data :The Iris Data Set , Visualization ,OLAP and Multidimensional Data Analysis • Classification: Basic Concepts, Decision Trees, and Model Evaluation • Classification: Alternative Techniques , Rule-Based Classifier , Bayesian , Bayesian Belief Networks • Association Analysis: Algorithms , Frequent Itemset Generation ,Rule Generation • Association Analysis: Categorical , Continuous Attributes (discretization and statistic based methods) , sequential Patterns • Cluster Analysis: Algorithms , K-means , Hierarchical, Cluster Evaluation