Automated Species Identification System using Machine Learning Techniques

Taxonomy is the science of naming, describing and classifying organisms that includes all plants, animals and microorganisms of the world. Using morphological, behavioral, genetic information and biochemical observations, taxonomists identify and describe species into classifications, including those that are new to science. The taxonomic identification of fishes is a time-consuming process and making errors is indispensable for those who are not specialists. This paper will present a hybrid approach to identify taxonomic characters of known species based on specimen and provide statistical clues for assisting taxonomists to identify accurate species or revision of misdiagnosed species. Two machine learning techniques, Random Forest and Naïve Bayes are used to build this approach. And then compare the classification accuracy of propose classifier with original approaches. KeywordsTaxonomy; Random Forest; style; Naïve Bayes; insert (key words)