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The comparison of the predicted densities with those obtained by measurement confirmed the reliability of the neural network and the group contribution method with average absolute errors of 0.14 and 2.03%, respectively.
The dendrograms were constructed after image capture and analysis by Pearson's correlation coefficients (r), and cluster analysis was performed by the unweighted pair group method with average linkages (UPGMA) using BioNumerics software (Applied Maths, Ghent, Belgium).
Cluster analysis of the histology patterns was performed with the BioNumerics software, version 4.0 (Applied Maths, Kortrijk, Belgium) using the unweighted pair group method with average linkages (UPGMA) and the Dice coefficient to analyze the similarities of the patterns.
Dendrograms were constructed after image capture and analysis by Pearson correlation coefficients (r), and cluster analysis was performed using the unweighted pair group method with average linkages (UPGMA), using BioNumerics software (Applied Maths, Ghent, Belgium).
The cluster analysis was performed using a hierarchical method with average linkage and Euclidean distance metrics.
In this setup, the combined PCFG was the best method with average A U C R O C of 0.58.
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The chemical variability of the essential oils among samples was assessed by linear discriminant analysis and UPGMA (unweighted pair-group method with averaging) cluster analysis.
A dendogram was generated using Dice similarity coefficients and unweighted pair group method with averages (1.5% tolerance, 1.5% optimization).
A dendrogram was constructed with Dice similarity coefficients and unweighted pair group method with averages (UPGMA).
From the similarity matrix, a dendrogram was constructed using the unweighted pair group method with averages.
Clustering was based on the unweighted pair-group method with averages (UPGMA), setting tolerance and optimization each at 1.5%.
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