How do I choose the right value for k in K-means clustering?
An example of an AI chatbot conversation about selecting the optimal k in K-means clustering.
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 data points, and the desired number of clusters.
Is there a method to determine the optimal k value?
Yes, the Elbow Method and the Silhouette Score are popular techniques to help determine the optimal k.
Can you explain the Elbow Method?
Sure! The Elbow Method involves plotting the explained variance against the number of clusters and looking for a 'knee' point.
What if the Elbow Method doesn't give a clear answer?
If it's unclear, you can try the Silhouette Score, which measures how similar an object is to its own cluster compared to other clusters.
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