|  | Name: | Data Mining | 
|  | No.: | S081104ZJ018 | Semester: | Autumn | 
|  | Hour: | 40 | Credit: | 2.0 | 
|  | Teacher: | Liu,Ying | 
|  | Introduction: | 
|  | Course Objective: Introduce the motivation of data mining, and the principles and main algorithms in data mining. The topics include: the major applications, characteristics, data warehouse, association rules mining, classification, prediction, clustering, etc. English is the only official language allowed in this class. This course is to provide students with knowledge and hands-on experience. Prerequisite Data Structure, Algorithms, C/C++ Programming, Database.
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Chapter 1: Introduction Motivation, major issues, major applications, characteristics Chapter 2: Data warehouse Model, architecture, operations Chapter 3: Data pre-processing Data cleaning, data transformation, data reduction Chapter 4: Association Rules Apriori, single-pass frequent itemset mining, FP-Growth Chapter 5: Classification Decision tree, Bayesian Classifier, Classification by backpropagation, KNN classifier, statistical prediction models Chapter 6: Clustering Partitioning methods, hierarchical methods, density-based methods, grid-based methods 
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