MCQ on Clustering in Data Mining: Machine Learning

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MCQ on Clustering in Data Mining: If you are looking for Multiple Choice Questions of Clustering, then you are at the right place.

In this blog post, we have listed the most important MCQ on Clustering in Data Mining / Machine Learning. The MCQs in this post is bifurcated into two parts:

  1. MCQ on K-Means Clustering
  2. MCQ on Hierarchical Clustering

MCQ on K-Means Clustering

Question 1:

In the K-Means algorithm, we have to specify the number of clusters.

  • ​True
  • ​False

Question 2:

What metric can be used to find an optimal number of clusters ?

  • ​R Squared
  • ​MSE
  • ​WCSS

Question 3:

We can choose any random initial centroids at the beginning of K-Means.

  • ​True
  • ​False

Question 4:

In Python, what is the recommended init parameter to input ?

  • ​random
  • ​k-means++
  • ​inertia
  • ​boost

Question 5:

In R, what is a good function to plot clusters ?

  • ​plot
  • ​ggplot
  • ​clusplot
  • ​plotclus
  • ​clusterplot

MCQ on Hierarchical Clustering

Question 1:

What can we use in Hierarchical Clustering to find the right number of clusters ?

  • ​The Elbow Method
  • ​Decision Trees
  • ​Dendrograms
  • ​Histograms

Question 2:

On which metric are based dendrograms ?

  • ​Within-cluster sum of squares
  • ​Within-cluster variance
  • ​MSE
  • ​RMSE

Question 3:

Hierarchical Clustering performs better than K-Means on large datasets

  • ​True
  • ​False

Question 4:

In Python, what is the class used to fit hierarchical clustering to a dataset ?

  • ​HierarchicalClustering
  • ​HClustering
  • ​AgglomerativeClustering
  • ​AgglomerativeHierarchical

Question 5:

In R, which function can be used to fit hierarchical clustering to a dataset ?

  • ​hc
  • ​cutree
  • ​hierachical
  • ​hclust
  • ​clusplot

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