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Updated: Mar 27, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
A Monte Carlo Study of the Recovery of Cluster Structure in Binary Data by Hierarchical Clustering Techniques
Abstract:
A Monte Carlo study was made of the recovery of cluster structure in binary data by five hierarchical techniques, with a view to finding which data structure factors influenced recovery and to determining differences between clustering methods with respect to these factors. Recovery was found to increase as the number of groups decreased, as the number of variables increased, as the mixing proportions tended towards equality, and as the number of observations was increased. Single link was found to be much worse than the other clustering techniques.
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