Abstract: A method implements an unsupervised and nonparametric approach for visualizing outliers by invariant detection scoring. The method includes receiving a selection of input data comprising a plurality of input values. The method further includes processing the input data to generate a distance matrix. The method further includes processing the distance matrix to generate neighborhood cumulative distribution function (NCDF) curves. The method further includes processing the NCDF curves to generate scores. The method further includes processing the scores to identify an anomalous value, in the input data, that corresponds to a score, of the scores, meeting a criterion.