Computer Science
University of the Cumberlands Data Mining Questions Discussion

University of the Cumberlands

Question Description

I’m studying for my Computer Science class and don’t understand how to answer this. Can you help me study?

Answer the following questions. Please ensure to use the Author, YYYY APA citations with any content brought into the assignment.

  1. For sparse data, discuss why considering only the presence of non-zero values might give a more accurate view of the objects than considering the actual magnitudes of values. When would such an approach not be desirable?
  1. Describe the change in the time complexity of K-means as the number of clusters to be found increases.
  1. Discuss the advantages and disadvantages of treating clustering as an optimization problem. Among other factors, consider efficiency, non-determinism, and whether an optimization-based approach captures all types of clusterings that are of interest.
  1. What is the time and space complexity of fuzzy c-means? Of SOM? How do these complexities compare to those of K-means?
  1. Explain the difference between likelihood and probability.
  1. Give an example of a set of clusters in which merging based on the closeness of clusters leads to a more natural set of clusters than merging based on the strength of connection (interconnectedness) of clusters.

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1. Assenting only the existence of non-zero values in sparse data might give a more
authentic view of objects than discussing the precise magnitude of values. The addition of zeros
in a set of data makes the data almost hard to account for it. When the zeros in the collection of
data continue to exceed, there is the likelihood of errors and inaccurate outcomes from the data.
Consequently, displaying the data using a graph will make it easy to look into and more presentable
compared to when zeros are incorporated hence making the chart appear vague (Tan et al., 2005).
It may not be wise to consider only the existence of a non-zero approach when conducting a
clustering analysis. The re...

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