In　evidential　clustering,　cluster-membership　uncertainty　is　represented　by　Dempster-Shafer　mass　functions.　The　notion　of　evidential　partition　generalizes　other　soft　clustering　structures　such　as　fuzzy,　possibilistic,　or　rough　partitions.　In　this　paper,　we　propose　two　extensions　of　the　Rand　index　for　evaluating　and　comparing　evidential　partitions,　called　similarity　and　consistency　indices.　The　similarity　index　is　suitable　for　measuring　the　closeness　of　two　soft　partitions,　whereas　the　consistency　index　allows　one　to　assess　the　agreement,　or　lack　of　conflict,　between　a　soft　partition　and　the　true　hard　partition.　Simulation　experiments　illustrate　some　applications　of　these　indices.