Transcription of Data Mining: Concepts and Techniques
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Data Mining: Concepts and Techniques
Data Mining: Concepts andTechniques3rd EditionSolution ManualJiawei Han, Micheline Kamber, Jian PeiThe University of Illinois at Urbana-ChampaignSimon Fraser UniversityVersion January 2, 2012c Morgan Kaufmann, 2011 For Instructors' references not copy! Do not distribute!iiPrefaceFor a rapidly evolving field like data mining, it is difficult to compose typical exercises and even moredifficult to work out standard answers. Some of the exercises inData Mining: Concepts and Techniquesare themselves good research topics that may lead to future Master or theses. Therefore, our solutionmanual is intended to be used as a guide in answering the exercises of the textbook. You are welcome toenrich this manual by suggesting additional interesting exercises and/or providing more thorough, or betteralternative we have done our best to ensure the correctness of the solutions, it is possible that some typos orerrors may exist.
and correlation analysis, classification, regression, clustering, and outlier analysis. Give examples of each data mining functionality, using a real-life database that you are familiar with. Answer: Characterization is a summarization of the general characteristics or …
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