Journal of Geological Society of India (Online archive from Vol 1 to Vol 78)

S. K. Parcha ¹, S. V. Sabnis ², P. K. Saraswati ³

Affiliations
1 Wadia Institute of Himalayan Geology, Dehra Dun - 248 001, IN
2 Department of Mathematics, Indian Institute of Technology Bombay, Powai, Mumbai - 400 076, IN
3 Department of Earth Sciences, Indian Institute of Technology Bombay, Powai, Mumbai - 400 076, IN

Abstract

The morphological variables often have non-normal distribution The statistical analysis of such variables by imposing normal assumption invariably yields unreliable results Classification and Regression Trees (CART) and Random Forests (RF) are non parametric techniques that are alternative to conventional classification methods such as cluster analysis and linear discriminant analysis used in morphometric research This paper uses the aforementioned Non-Parametric techniques to the variables of the cramdial features of the trilobite genera Hundwarella and Iranoleesia. It is found that misclassification rates in CART and cluster analyses are comparable, whereas they are reduced substantially by the use of Random Forests.

Keywords

Taxonomy, Trilobites, Cambrian, Random Forests, Regression Tree, Morphometries.

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