Divide and conquer! Data-mining tools and sequential multivariate analysis to search for diagnostic morphological characters within a plant polyploid complex (Veronica subsect. Pentasepalae, Plantaginaceae).

ABSTRACT: This study exhaustively explores leaf features seeking diagnostic characters to aid the classification (assigning cases to groups, i.e. populations to taxa) in a polyploid plant-species complex. A challenging case study was selected: Veronica subsection Pentasepalae, a taxonomically intricate group. The "divide and conquer" approach was implemented-that is, a difficult primary dataset was split into more manageable subsets. Three techniques were explored: two data-mining tools (artificial neural networks and decision trees) and one unsupervised discriminant analysis. However, only the decision trees and discriminant analysis were finally used to select diagnostic traits. A previously established classification hypothesis based on other data sources was used as a starting point. A guided di

SUBMITTER: Lopez-Gonzalez N 

PROVIDER: S-EPMC6025878 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature