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Which evaluation metrics are specific to clustering tasks?Review LaterAccuracy and precisionF1 score and recallSilhouette score and adjusted Rand indexMean squared error (MSE) and mean absolute error (MAE)

Question

Which evaluation metrics are specific to clustering tasks?Review LaterAccuracy and precisionF1 score and recallSilhouette score and adjusted Rand indexMean squared error (MSE) and mean absolute error (MAE)

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Solution

The evaluation metrics that are specific to clustering tasks are the Silhouette score and the adjusted Rand index.

  1. Silhouette Score: This metric calculates the mean distance between a sample and all other points in the next nearest cluster. The silhouette score ranges from -1 to 1, where a high value indicates that the object is well matched to its own cluster and poorly matched to neighboring clusters. If most objects have a high value, then the clustering configuration is appropriate. If many points have a low or negative value, then the clustering configuration may have too many or too few clusters.

  2. Adjusted Rand Index

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