Analyze what is time and space complexity of fuzzy c-means


Discussion Post

• 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?

• Describe the change in the time complexity of K-means as the number of clusters to be found increases.

• 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.

• What is the time and space complexity of fuzzy c-means? Of SOM? How do these complexities compare to those of K-means?

• Explain the difference between likelihood and probability.

• 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

The response must include a reference list. Using Times New Roman 12 pnt font, double-space, one-inch margins, and APA style of writing and citations.

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Basic Statistics: Analyze what is time and space complexity of fuzzy c-means
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