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This project uses the K-Nearest Neighbors (KNN) algorithm to classify Iris flowers based on their sepal and petal measurements. The dataset used in this project is the Iris Dataset, which includes 150 samples of Iris flowers, each with four features: sepal length, sepal width, petal length, and petal width.
Iris flower has three species; setosa, versicolor, and virginica, which differs according to their measurements. Now assume that you have the measurements of the iris flowers according to their species, and the task is to train a machine learning model that can learn from the measurements of the iris species and classify them.