What factors should I consider when choosing the value of k for K-means clustering?
You should consider the size of your dataset, the distribution of your data, and the desired number of clusters.
Are there any methods to help determine the best value of k?
Yes, methods like the Elbow Method, Silhouette Score, and Gap Statistic can help you find the optimal k.
Can you explain the Elbow Method in more detail?
Sure! The Elbow Method involves plotting the explained variance against the number of clusters and looking for a 'knee' point.
What if I choose a value of k that is too high or too low?
Choosing a k that is too high can lead to overfitting, while a k that is too low may oversimplify the data.
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