Iris-Flower-Classification

PROBLEM STATEMENT: Identifying species of Iris flowers manually using petal and sepal measurements can be time-consuming and prone to human error. A smart classification system is needed to help automate the process of identifying Iris flower species with high accuracy using machine learning.

PROPOSED SOLUTION Develop a machine learning model to classify Iris flowers into three species — Setosa, Versicolor, and Virginica—based on petal and sepal length and width.�

The system will: Use the popular Iris dataset Preprocess and visualize data Train a classification model (e.g., Logistic Regression or Decision Tree) Predict the species of a flower given new input data