How to Choose K value in K means? if there are any techniques, name them and explain.

Question

Accepted Answer

Choosing the optimal K value in K-means clustering is crucial for accurate results.

Elbow method: Plotting the sum of squared distances vs. K and selecting the K value where the curve bends like an elbow.
Silhouette method: Calculating the average silhouette score for different K values and choosing the one with the highest score.
Gap statistic method: Comparing the within-cluster dispersion to a reference null distribution to find the optimal K value.
Cross-validation: Splitting the data into training and validation sets to evaluate the performance of different K values.
Domain knowledge: Understanding the problem domain and considering the practical implications of different K values.

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