Data Science Multiple Choice Questions on “Clustering”.
1. K-means is not deterministic and it also consists of number of iterations.
a) True
b) False
Answer: a
Explanation: K-means clustering produces the final estimate of cluster centroids.
2. Point out the correct statement.
a) The choice of an appropriate metric will influence the shape of the clusters
b) Hierarchical clustering is also called HCA
c) In general, the merges and splits are determined in a greedy manner
d) All of the mentioned
Answer: d
Explanation: Some elements may be close to one another according to one distance and farther away according to another.
3. Which of the following is finally produced by Hierarchical Clustering?
a) final estimate of cluster centroids
b) tree showing how close things are to each other
c) assignment of each point to clusters
d) all of the mentioned
Answer: b
Explanation: Hierarchical clustering is an agglomerative approach.
4. Which of the following is required by K-means clustering?
a) defined distance metric
b) number of clusters
c) initial guess as to cluster centroids
d) all of the mentioned
Answer: d
Explanation: K-means clustering follows partitioning approach.
5. Point out the wrong statement.
a) k-means clustering is a method of vector quantization
b) k-means clustering aims to partition n observations into k clusters
c) k-nearest neighbor is same as k-means
d) none of the mentioned
Answer: c
Explanation: k-nearest neighbor has nothing to do with k-means.
6. Which of the following combination is incorrect?
a) Continuous – euclidean distance
b) Continuous – correlation similarity
c) Binary – manhattan distance
d) None of the mentioned
Answer: d
Explanation: You should choose a distance/similarity that makes sense for your problem.
7. Hierarchical clustering should be primarily used for exploration.
a) True
b) False
Answer: a
Explanation: Hierarchical clustering is deterministic.
8. Which of the following function is used for k-means clustering?
a) k-means
b) k-mean
c) heatmap
d) none of the mentioned
Answer: a
Explanation: K-means requires a number of clusters.
9. Which of the following clustering requires merging approach?
a) Partitional
b) Hierarchical
c) Naive Bayes
d) None of the mentioned
Answer: b
Explanation: Hierarchical clustering requires a defined distance as well.