What is the best way to determine the k-value in k-means clustering?
An example of an AI chatbot conversation about determining the optimal k-value in k-means clustering.
What is the best way to determine the k-value in k-means clustering?
A common method is the Elbow Method, where you plot the explained variance against the number of clusters.
How does the Elbow Method work?
You calculate the sum of squared distances from each point to its assigned cluster center for different k values.
What should I look for in the plot?
Look for a point where the rate of decrease sharply changes, forming an 'elbow' shape. This point suggests a good k.
Are there other methods to determine k?
Yes, methods like the Silhouette Score and Gap Statistic can also help in determining the optimal k-value.
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