What is the elbow method in clustering?
An example of an AI chatbot conversation about the elbow method in clustering analysis.
Can you explain what the elbow method is in clustering?
The elbow method is a technique used to determine the optimal number of clusters in a dataset.
How does the elbow method work?
It works by plotting the explained variance against the number of clusters and looking for the 'elbow' point.
What does the 'elbow' point signify?
The 'elbow' point indicates the number of clusters where adding more clusters doesn't significantly improve the model.
Can you give an example of how to apply the elbow method?
Sure! You can use it with K-means clustering by plotting the sum of squared distances for different cluster counts.
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