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An Efficient Neuro-Fuzzy Approach for Classification of Iris Dataset
Conference proceeding

An Efficient Neuro-Fuzzy Approach for Classification of Iris Dataset

Vaishali Arya, R. K. Rathy and IEEE
PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON RELIABILTY, OPTIMIZATION, & INFORMATION TECHNOLOGY (ICROIT 2014), pp.161-165
01/01/2014

Abstract

Computer Science Computer Science, Interdisciplinary Applications Engineering Engineering, Electrical & Electronic Science & Technology Technology
Various classification models exist for classifying the Iris Dataset using Neuro-Fuzzy Approach [1][2][3][4]. All had classified into three classes, named as Setosa, Virginica and Versicolour based on the parameters of flower measured in cms. The analysis of these results show a limited success as the classification has found to be non-linear. We have attempted with four parameters with neuro-fuzzy classification and have obtained the classification results with much higher accuracy.

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