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Which of the following is a disadvantage of the K-means algorithm?
Which of the following is a disadvantage of the K-means algorithm?
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Practice Questions
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Q1
Which of the following is a disadvantage of the K-means algorithm?
It can handle large datasets efficiently
It requires the number of clusters to be specified in advance
It is sensitive to outliers
It can be used for both supervised and unsupervised learning
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A key disadvantage of K-means is that it requires the user to specify the number of clusters beforehand, which may not always be known.
Questions & Step-by-step Solutions
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Q
Q: Which of the following is a disadvantage of the K-means algorithm?
Solution:
A key disadvantage of K-means is that it requires the user to specify the number of clusters beforehand, which may not always be known.
Steps: 4
Show Steps
Step 1: Understand what K-means algorithm is. It is a method used to group data into clusters.
Step 2: Know that when using K-means, you need to decide how many clusters (groups) you want to create before starting.
Step 3: Realize that sometimes you may not know the best number of clusters to use for your data.
Step 4: Recognize that this requirement to choose the number of clusters in advance can be a disadvantage of the K-means algorithm.
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