K-Means clustering algorithm to cluster multi class data set

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Reference no: EM132450986

Data Mining Text book: Introduction to data mining 2nd ed. Boston: Pearson, 2019: pang-ning tan, michael steinbach, vipin kumar

1. Compare different Ensemble methods with appropriate examples.

2. Discuss the strengths and weaknesses of using K-Means clustering algorithm to cluster multi class data sets. How do you compare it with a hierarchical clustering technique.

3. Compare and contrast the different techniques for anomaly detection that were presented in Chapter 9. Discuss techniques for combining multiple anomaly detection techniques to improve the identification of anomalous objects.

Organization Leadership & Decision-Making Text book: James D. McKeen, Heather A. Smith, IT Strategy: Issues and Practices, Third Edition. Pearson, 2015, ISBN-13 978-0-13-354424-4.

4. Read the Consumerization of Technology at IFG Case Study on pages 239-242 in the textbook. Answer the Discussion Questions at the end of the Case Study.

5. Read the Innovation at International Foods Case Study on pages 234-238 in the textbook. Answer the Discussion Questions at the end of the Case Study. Your responses must be complete, detailed and in APA format. See the sample assignment for expected format and length. The grading rubric is included below.

Reference no: EM132450986

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