Since it is an AI programme, keep to the most basic algorithm that can be made to perform reasonably well in a dataset, i.e. The aim is to develop a classifier that accurately classifies a flower as one of the three classes based on the given four features. The Iris Flower Classification contains 150 instances of flower, where each flower involves four attributes: sepal length, sepal width, petal length, and petal width (each in cm) and three classes that belong to setosa, vermicolor, and virginica. This is a beginner’s introduction to the AI world - Iris Flowers Classification Problem. In addition, we will provide step-by-step guidance on how to go about approaching a particular problem. ![]() ![]() In this article, we will be focusing on the models and algorithms that work on real data and produce results. Well-written code can be found anywhere, but it lacks methodology, which is the most important thing in learning to write a program.
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