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K-medoids Clustering Quiz

Authored by M. GOVINDARAJ CDOE

Computers

University

K-medoids Clustering Quiz
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14 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary goal of partitioning clustering?

Maximize similarity between different clusters

Minimize the number of clusters

Maximize similarity within each cluster

Minimize the distance between all data points

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is NOT a popular partitioning method?

k-means clustering

Hierarchical clustering

k-medoids clustering

CLARA clustering

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In k-medoids clustering, what does a 'medoid' represent?

The mean of the cluster

A random data point

An actual data point in the cluster

The centroid of the cluster

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the first step in the k-medoids clustering process?

Randomly select k data points as medoids

Compute the total cost of clustering

Update the medoids

Assign points to the closest medoid

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which distance metric is commonly used in k-medoids clustering?

Euclidean distance

Cosine similarity

Manhattan distance

Hamming distance

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a disadvantage of k-medoids clustering?

Less interpretability

Higher computational complexity

Robustness to outliers

Applicability to arbitrary distance metrics

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How is the total cost of clustering computed in k-medoids?

By minimizing the distances between clusters

By averaging the distances within clusters

By summing the distances to the medoids

By summing the distances between all points

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