An efficient Neuro-Fuzzy Approach for classification of Iris Dataset

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.