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
In the K-Means algorithm, we have to specify the number of clusters.
What metric can be used to find an optimal number of clusters ?
- R Squared
We can choose any random initial centroids at the beginning of K-Means.
In Python, what is the recommended init parameter to input ?
In R, what is a good function to plot clusters ?
MCQ on Hierarchical Clustering
What can we use in Hierarchical Clustering to find the right number of clusters ?
- The Elbow Method
- Decision Trees
On which metric are based dendrograms ?
- Within-cluster sum of squares
- Within-cluster variance
Hierarchical Clustering performs better than K-Means on large datasets
In Python, what is the class used to fit hierarchical clustering to a dataset ?
In R, which function can be used to fit hierarchical clustering to a dataset ?
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.