What is a primary advantage of using hierarchical clustering over K-means?
Practice Questions
Q1
What is a primary advantage of using hierarchical clustering over K-means?
It does not require the number of clusters to be specified in advance
It is faster than K-means
It can handle large datasets more efficiently
It is less sensitive to noise
Questions & Step-by-Step Solutions
What is a primary advantage of using hierarchical clustering over K-means?
Step 1: Understand what clustering is. Clustering is a way to group similar items together.
Step 2: Learn about K-means clustering. K-means requires you to decide how many groups (clusters) you want before starting.
Step 3: Know about hierarchical clustering. Hierarchical clustering builds a tree of clusters without needing to set the number of clusters in advance.
Step 4: Recognize the advantage. Since hierarchical clustering does not need a fixed number of clusters, it allows you to explore different groupings and find the best fit.
