iris data (24 pts) using the iris data explained in the chapter, show that those

Question

iris data (24 pts) using the iris data explained in the chapter, show that those rules below can be derived: ta set: (UCI Machine Learning Repository) : /hrurw.ics.uci.edu/-mlearn s://archive.ics.uci.edu/ml/datasets/Iris a set attributes - The species of a flower - Sepal width -Sepal length - Petal length- Categories: -low, medium, high 1O, 2.5), [2.5,5), I5.00) - Petal width - Categories: -low, medium, high-=> [0, 0.75), [0.75, 1.75), [1.75, 99) Rules can be derived: -Petal width low and petal length low Setosa - Petal width medium - Petal width high and petal length high Virginica and petal length medium Versicolour

Explanation / Answer

Hi,

So basically this is a very typical Supervised learning Classification problem.

You have been given a dataset called the Iris dataset. In there you would find columns as mentioned above and a class label saying Sentosa, Versicolor and Virginica.

The main aim of this project is to train a model for the entire data using a supervised classification algorithm such as Naive Bayes, Decision Trees, Support Vector machines, etc.

Once the model has been trained, it is time to test the model.

There are 3 test cases required in your project as mentioned in the rules that can be derived.

When you have a specified petal width and petal length given, you must get the class label as stated beside it.

Once you get all the test cases right, your model has been trained properly and you arr set to go.

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