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An Approach for IRIS Plant Classification Using Neural Network

Author(s): Madhusmita Swain | Sanjit Kumar Dash | Sweta Dash | Ayeskanta Mohapatra

Journal: International Journal on Soft Computing
ISSN 2229-7103

Volume: 3;
Issue: 1;
Start page: 79;
Date: 2012;
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Keywords: IRIS dataset | artificial neural networks | Back-propagation algorithm

Classification is a machine learning technique used to predict group membership for data instances. Tosimplify the problem of classification neural networks are being introduced. This paper focuses on IRIS plant classification using Neural Network. The problem concerns the identification of IRIS plant species on the basis of plant attribute measurements. Classification of IRIS data set would be discovering patterns from examining petal and sepal size of the IRIS plant and how the prediction was made from analyzing the pattern to form the class of IRIS plant. By using this pattern and classification, in future upcoming years the unknown data can be predicted more precisely. Artificial neural networks have been successfully applied to problems in pattern classification, function approximations, optimization, and associative memories. In this work, Multilayer feed- forward networks are trained using back propagation learning algorithm.

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