Adjusted Rand Index Measure
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An Adjusted Rand Index Measure is an external clustering evaluation measure that measures clustering similarity between two clustering partitions adjusted for chance agreement.
- AKA: ARI Measure, Adjusted Rand Measure, Chance-Corrected Rand Index.
- Context:
- It can typically compare unsupervised clustering output with ground truth labels.
- It can typically assess clustering agreement through pairwise comparisons.
- It can typically normalize Rand Index values using expected value correction.
- It can often evaluate legal document clustering tasks for quality assessment.
- It can often complement Normalized Mutual Information Measure in clustering evaluation.
- It can range from being a Negative Adjusted Rand Index Measure to being a Perfect Adjusted Rand Index Measure, depending on its agreement level.
- It can range from being a Binary Adjusted Rand Index Measure to being a Multi-Class Adjusted Rand Index Measure, depending on its cluster count.
- It can range from being a Balanced Adjusted Rand Index Measure to being a Imbalanced Adjusted Rand Index Measure, depending on its cluster distribution.
- It can range from being a Small-Dataset Adjusted Rand Index Measure to being a Large-Dataset Adjusted Rand Index Measure, depending on its data scale.
- ...
- Examples:
- Legal Clustering Evaluations, such as:
- Benchmark Evaluations, such as:
- ...
- Counter-Examples:
- Silhouette Coefficient Measure, which is an internal measure.
- Raw Rand Index, which lacks chance correction.
- Accuracy Measure, which applies to supervised tasks.
- See: External Clustering Evaluation Measure, Clustering Evaluation Measure, Rand Index, Normalized Mutual Information Measure, Clustering Task, Cluster Purity Measure, F-Score Measure, Contingency Table, Pairwise Comparison.