Classification of Iris Flower by Random Forest Algorithm

Abstract

With the introduction of artificial intelligence into our lives, artificial intelligence researches and applications in different fields such as agriculture, health, military and engineering applications have become very popular iris flower was classified using the popular Random Forest, support vector machine and Artificial neural network machine learning classifiers with high accuracy rates. As a result of the classification, the performance of the trained models was evaluated according to the confusion matrix, sensitivity, specificity, accuracy, F1 score, ROC curve and AUC evaluation criteria. The random forest algorithm was the most successful among the trained algorithms with an accuracy rate of 97%.