Introduction <> Questions 1) Sequential pattern mining is a topic of data mining concerned with finding statistically relevant patterns between data examples where the values are delivered in a sequence. Discuss what is sequential data? What is sequential pattern mining? Explain difference between classification and clustering in data mining. 2) Consider the mean of a cluster of objects from a binary transaction data set. What are the minimum and maximum values of the components of the mean? What is the interpretation of components of the cluster mean? Which components most accurately characterize the objects in the cluster? Conclusion <> Grading Rubric for DF5 Providing a comprehensive discussion of the topic: 25 percent Justifying ideas and responses by using appropriate examples and references from texts, Web sites, other references, or personal experience and cited the sources in the correct: 25 percent Commented on at least two of your classmates’ postings in a meaningful way at least 100 words: 25 percent Filling the number of required 200 words or more for the discussion: 25 percent

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