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:
- MCQ on K-Means Clustering
- 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
More Related MCQs
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Dr. Sunny is an Assistant Professor in higher education. He has completed his Ph.D. He has a depth of knowledge in the research field and in higher education.