Minimal spanning tree clustering of gas chromatographic liquid phases

Abstract A minimal spanning tree clustering algorithm is applied to gas chromatographic liquid phases. The tree is broken according to a rule which depends upon nearest neighbor information. The resulting minimal spanning tree divides the liquid phases into 13 clusters which vary in size from seven to 27 phases. Forty-one phases are designated as outliers in this analysis.

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