Split conformal clustering with stochastic labels provides finite-sample marginal coverage guarantees for cluster label confidence sets, controlled by soft-label consistency and replace-one stability of the clustering algorithm.
Semi-supervised conformal prediction with unlabeled nonconformity score.arXiv:2505.21147
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Inference for Clustering: Conformal Sets for Cluster Labels
Split conformal clustering with stochastic labels provides finite-sample marginal coverage guarantees for cluster label confidence sets, controlled by soft-label consistency and replace-one stability of the clustering algorithm.