On the Use of the Adjusted Rand Index as a Metric for Evaluating Supervised Classification

By Jorge M. Santos, Mark J. Embrechts. International Conference on Artificial Neural Networks, 2009

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Activity recognition in beach volleyball using a Deep Convolutional Neural Network (2017, methodology): “The feature selection was performed with a filter approach based on the adjusted rand index (ARI, Santos and Embrechts 2009).”
Sequence Synopsis: Optimize Visual Summary of Temporal Event Data (2018, unknown): “5 means that the results are very similar [39].”
A Comparison Study on Similarity and Dissimilarity Measures in Clustering Continuous Data (2015, methodology): “Although there are different clustering measures such as Sum of Squared Error, Entropy, Purity, Jaccard etc. but among them the Rand index is probably the most used index for cluster validation [17,41,42].”
HELoC: Hierarchical Contrastive Learning of Source Code Representation (2022, methodology): “To evaluate the code clustering effectiveness of HELoC, we use Adjusted Rand Index (ARI) [63] as the metric.”
Structured labeling for facilitating concept evolution in machine learning (2014, methodology): “We computed label consistency via the Adjusted Rand Index (ARI) [17], a common and recommended metric for computing agreement between some partitioning of data (defined by participant labels in our case) and some ground truth (defined by data our coders agreed upon) by examining pairs [25].”