This article handles the problem of validating the results of nested (as opposed to “flat”) clusterings. It shows that standard external validation indices used for partitioning clustering validation, like Rand statistics, Hubert Γ statistic or F-measure are not applicable in nested clustering cases. Additionally to the work, where F-measure was adopted to hierarchical classification as hF-measure, here some methods to get desired hRand and hΓ indices for nested clustering are presented. Introduced measures are evaluated and, as an exemplary application, a validation of nested clustering methods for Wikipedia articles using OPTICS algorithm is shown.