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Kai Klede

2 accepted papers

2023

$p$-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison

NeurIPS 2023poster

Popular metrics for clustering comparison, like the Adjusted Rand Index and the Adjusted Mutual Information, are type II biased. The Standardized Mutual Information removes this bias but suffers from counterintuitive non-monotonicity and poor computational efficiency. We introduce the $p$-value adju…

2023

FastAMI – a Monte Carlo Approach to the Adjustment for Chance in Clustering Comparison Metrics

AAAI 2023technical

Clustering is at the very core of machine learning, and its applications proliferate with the increasing availability of data. However, as datasets grow, comparing clusterings with an adjustment for chance becomes computationally difficult, preventing unbiased ground-truth comparisons and solution s…