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Updated: May 29, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
PFS Clustering Method
Abstract:
This paper presents a method of cluster analysis based on a pseudo F-statistic (PFS) criterion function. It is designed to subdivide an ensemble into an optimal set of groups, where the number of groups is not specified and no ad hoc parameters are employed. Univariate and multivariate F-statistic and pseudo F-statistic consistency is displayed. Algorithms for feasible application of PFS are given. Results from simulations are utilized to demonstrate the capabilities of the PFS clustering method and to provide a comparative guide for other users.
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