What are the techniques in handling categorical attributes


Assignment:

Question1: After reviewing the case study this week by Krizanic (2020), answer the following questions in format.

What is the definition of data mining that the author mentions? How is this different from our current understanding of data mining?

What is the premise of the use case and findings?

What type of tools are used in the data mining aspect of the use case and how are they used?

Were the tools used appropriate for the use case? Why or why not?

Discussion 1

What are the techniques in handling categorical attributes?

How do continuous attributes differ from categorical attributes?

What is a concept hierarchy?

Note the major patterns of data and how they work.

Discussion 2

This week we also discuss the concepts in chapter seven, which deals with the basic concepts and algorithms of cluster analysis. After reading chapter seven answer the following questions:

What is K-means from a basic standpoint?

What are the various types of clusters and why is the distinction important?

What are the strengths and weaknesses of K-means?

What is a cluster evaluation?

Select at least two types of cluster evaluations, discuss the concepts of each method.

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Data Structure & Algorithms: What are the techniques in handling categorical attributes
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