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Tectonic discrimination of basalts with classification trees
manuscript accepted for publication in Geochimica et Cosmochimica Acta
Pieter Vermeesch
Department of Geological and Environmental Sciences, Stanford University
Currently at Institute of Isotope Geology and Mineral Resources, ETH Zürich, Switzerland
Abstract:
Traditionally, geochemical classification of basaltic rocks of unknown
tectonic affinity has been performed by discrimination diagrams.
Although easy to use, this method is fairly inaccurate because it only
uses bi- or trivariate data. Furthermore, many popular discrimination
diagrams are statistically not very rigorous because the decision
boundaries are drawn by eye, and they ignore closure, thus violating
the rules of compositional data analysis. Classification trees
approximate the data space by a stepwise constant function, and are a
more rigorous and potentially more effective way to determine tectonic
affinity. Trees allow the simultaneous use of an unlimited number of
geochemical features, while still permitting visualization by an
easy-to-use, two-dimensional graph. Two classification trees are
presented for the discrimination of basalts of mid-ocean ridge (MORB),
ocean island (OIB) and island arc (IAB) affinities. The first tree
uses 51 major, minor and trace elements and isotopic ratios and should
be used for the classification of fresh basalt samples. A second tree
only uses high field strength (HFS) element analyses and isotopic
ratios, and can also be used for basalts that have undergone
alteration. The probability of successful classification is 89% for
the first and 84% for the second tree, as determined by ten-fold
cross-validation. Even though the trees presented in this paper use
many geochemical features, it is not a problem if some of these are
missing in the unknown sample. Classification trees solve this
problem with surrogate variables, which give more or less the same
decision as the primary variables. The advantages of the
classification tree approach over discrimination diagrams are
illustrated by a comparative test on a sample dataset of known
tectonic affinities. Although arguably better than discrimination
diagrams, classification trees are not perfect, and the limitations of
the method are illustrated on a published dataset of basalts from the
Pindos Basin (Greece).
Next: INTRODUCTION
Pieter Vermeesch
2005-12-14