Iris Flower Classification

Let’s assume that a hobby botanist is interested in distinguishing the species of some iris flowers that she has found. She has collected some measurements associated with each iris, which are: the length and width of the petals the length and width of the sepals, all measured in centimetres. She also has the measurements of some irises that have been previously identified by an expert botanist as belonging to the species setosa, versicolor, or virginica. For these measurements, she can be certain of which species each iris belongs to. We will consider that these are the only species our botanist will encounter. The goal is to create a machine learning model that can learn from the measurements of these irises whose species are already known, so that we can predict the species for the new irises that she has found.

Data source

https://www.kaggle.com/arshid/iris-flower-dataset

Objectives

Be able to predict the species of a flower based on its sepal and petal measurments

Classification models used

• Kneighborsclassifier
• Logisticregression
• Decisiontreeclassifier
• Svc-svm
• Xgbclassifier
• Randomforestclassifier