What are some common evaluation metrics in clustering?
Since there are no labels associated with the observations in unsupervised learning, there is no direct error metric that can be applied
Since there are no labels associated with the observations in unsupervised learning, there is no direct error metric that can be applied
The WCSS is a measure of the variability of observations within clusters.
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The Rand Index can be used for comparing the results from multiple clustering algorithms.
The ARI adjusts the raw Rand Index for classification by chance by subtracting the expected index from both the numerator and denominator.
Silhouette Score compares the distance of observations to the centroids of the clusters they are assigned to against that to the centroids of other clusters in an algorithm like K-Means.
The Dunn Index is a ratio of the smallest distance between observations assigned to different clusters over the largest distance between observations assigned to the same cluster.
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