Cite this Article

M. Narasimha Rao, G. Srikar, Md. Zubair Ahmed, T. Sai Yashwanth, 2025. "IRIS Flower Classification Using Machine Learning", International Journal of Emerging Information Technology (IJEIT) 1(1): 22-31.

Keywords

Botany, Setosa, Versicolor, Virginica.

Abstract

Iris flower group has 3 different species. 1. Setosa, 2. Versicolor, 3. Virginica. It is very difficult to classify the species by just looking at them and measuring their sepal and petals. Iris flower classification is useful for botany people to automate the process of Iris flower classification, so the work can be done easily, it is a foundational dataset for the learners to know and gain knowledge about classification of categories. This is very helpful for the research purposes, apart from this we can use this usecase as a benchmark for other classification problems in the real world. We explored the use of different algorithms and the advantages, disadvantages of each algorithm. Overall this study gives a thorough review of the work we have done.

Introduction

Iris is a flowering plant which has about 310 accepted Species. These flowers are grown in dry climates, from bulbs. They have long erect stems. There are 3 main species of iris. They are Setosa, Versicolor and Virginica. This is one of the 3 Different main species of Iris. Iris- versicolor. In this study we are going to use different machine learning algorithms to learn and predict. Then we are going to select the model which gives the maximum accuracy. In this study we are going to show the work we had done on the dataset and the process we followed to achieve the output and different models performance.