Conditioned data is generated from multi-dimensional data populations. The multi-dimensional data populations include time-based media data, such as video data, or data associated with time-based media. The conditioned data is scaled such that dimensions of greater distinguishability are emphasized. To generate the conditioned data, a data conditioner receives populations of multi-dimensional data that have the same dimensions in the data. Data of a dimension is scaled based on a distinguishability factor calculated for the dimension. The distinguishability factor is calculated based on distributions in the dimension for the data populations. The data conditioning approach is scalable to any number of data populations and any number of data dimensions.