Classification of Leaf Type Using Multilayer Perceptron, Naive Bayes and Support Vector Machine Classifiers

Azra Music, Sadina Gagula-Palalic


Multiclass classification has always been challenging in the area of machine learning algorithms. Different publicly available software applications offer various learning algorithms’ implementations. This paper uses leaf dataset with 30 different plant species with simple leaf types prepared by Silva et al (2014), and classification is performed using Multilayer Perceptron, Naive Bayes and Support Vector Machine classifiers. Performance of classifiers is compared based on time needed for building the model and classification accuracy.


Multiclass Classification; Neural Networks; Multilayer Perceptron; Naive Bayes; Leaf Dataset

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Copyright (c) 2016 Azra Music, Sadina Gagula-Palalic

ISSN 2233 -1859

Digital Object Identifier DOI: 10.21533/scjournal

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This work is licensed under a Creative Commons Attribution 4.0 International License