Regression tree analysis for the determinants of first detection location of invasive alien species.

Abstract

<p>A: using all explanatory variables; B: using explanatory variables except those classified into “IP” category (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031734#pone-0031734-t001" target="_blank">Table 1</a>). Each node of the tree is described by the splitting variable, its splitting criteria, percentage of variance the splitter explains, mean ± standard deviation for the number of first detection locations of invasive alien species, and the number of sample (i.e. species) at that node in brackets. (<i>Inset</i>) Cross-validation processes for selection of the best regression trees. Line shows a single representative 10-fold cross-validation of the most frequent (modal) best trees with standard error (SE) estimates of each tree size. Bar charts are the numbers of the optimal trees of each size (frequency of tree) selected from a series of 50 cross-validations based on the minimum cost tree, which minimizes the cross-validated relative error (white, SE rule 0), and 50 cross-validations based on the one-SE rule (gray, SE rule 1), which minimizes the cross-validated relative error within one SE of the minimum. The most frequent trees have four terminal nodes. See the legend of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031734#pone-0031734-g001" target="_blank">Fig. 1</a> for province codes.</p

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