What is the elbow method in clustering?
The elbow method is a technique used to determine the optimal number of clusters in a dataset by plotting the explained variance against the number of clusters.
How do I implement the elbow method?
To implement the elbow method, you calculate the sum of squared distances from each point to its assigned cluster center for different numbers of clusters and plot these values.
What does the 'elbow' in the graph represent?
The 'elbow' point in the graph indicates the optimal number of clusters, where adding more clusters yields diminishing returns in variance reduction.
Can you give an example of using the elbow method?
Sure! For instance, if you have a dataset of customer purchases, you can use the elbow method to find the best number of customer segments for targeted marketing.
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