Artificial Neural Network for Predicting Animals Category

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Abstract
Abstract: In this paper an Artificial Neural Network (ANN) model, was developed and tested for predicting the category of an animal. There is a number of factors that influence the classification of animals. Such as the existence of hair/ feather, if the animal gives birth or spawns, it is airborne, aquatic, predator, toothed, backboned, venomous, has –fins, has-tail, cat-sized, and domestic. They were then used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was developed and trained, using data set, which its title is “Zoo Data Set” and was obtained from Machine Learning Repository, and its created by Richard Forsyth. Test data evaluation shows that the ANN model is able to correctly predict the animal category with 100% accuracy.
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Archival date: 2019-02-25
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2019-02-25

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