pointoften

Pointoften is a term used in data analysis and visualization to describe the frequency with which individual data points appear across multiple resampled or perturbed representations of a dataset. The concept is informal and not part of a standardized vocabulary, but it is used in some contexts to assess the stability or representativeness of points in a dataset.

Definition and computation

Pointoften quantifies how often a given observation is included or assigned in repeated subsampling, bootstrapping, or clustering runs. If B resamples are generated and a point appears in k of them, its pointoften score is k divided by B (a value between 0 and 1). In clustering, the metric may be defined as the fraction of runs in which the point joins a particular cluster. Variants may apply different inclusion criteria or weight observations differently across runs.

Applications

The measure can help identify representative or stable observations, guide data reduction or visualization by highlighting high-frequency points, and support outlier detection through low pointoften values. It is sometimes used in stability assessments for clustering, feature selection, or ensemble methods to understand which points consistently influence results.

Limitations

Pointoften is not a standardized metric and depends on the sampling strategy, dataset size, and modeling approach. Interpretations can vary across methods, and biases in resampling can affect scores. It should be used alongside other diagnostics rather than as a sole criterion.

See also bootstrap, resampling, stability, consensus clustering.