What is Adjusted Rand Index (ARI)?
The ARI adjusts the raw Rand Index for classification by chance by subtracting the expected index from both the numerator and denominator.
The ARI adjusts the raw Rand Index for classification by chance by subtracting the expected index from both the numerator and denominator.
The Rand Index can be used for comparing the results from multiple clustering algorithms.
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.
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 WCSS is a measure of the variability of observations within clusters.
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Since there are no labels associated with the observations in unsupervised learning, there is no direct error metric that can be applied
In this approach, clusters are represented by parametric distributions, and the data is modeled as a mixture of the specified distributions.
Clustering is used to partition data set into N distinct groups/clusters. These groups are semantically coherent in nature
Exclusive Clustering, Probabilistic (Fuzzy) Clustering, Hierarchical Clustering, Model-based Clustering
Each observation is assigned to one or more clusters with a probability of belonging to each.
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