Iris Flower Species Identification Using Machine Learning Approach

Classification is one of the most important approach of machine learning. Main task of machine learning is data analysis. Various algorithms are available for classification like decision tree, Navie Bayes, Back propagation, Neural Network, Artificial Neural, Multi-layer perception, Multi class classification, Support vector Machine, K-nearest neighbor etc. In this paper, three methods are explained in detail. Implementation is done using iris dataset. Scikit tool is used for the implementation purpose. This paper mainly applies classification and regression algorithms on IRIS dataset, by discovering and analyzing the patterns, using sepal and petal size of the flower. We have found that SVM classifier gives best accuracy compared to KNN and logistic regression models.