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Question: Write a program to apply Machine Learning classification models to Iris flowers dataset. Follow the steps:
1. Download the iris.csv file. From this file the label (target) is defined with the ‘variety' column and the features with ‘epal.length', ‘sepal.width', ‘petal.length', ‘petal.width' columns.
2. Preprocess the iris.csv file by label encoding the target ‘variety' column.
3. Apply the following Machine Learning classification models: K Nearest Neighbors and Random Forests
4. Calculate the following classification metrics to validate the model: Accuracy Score, Confusion Matrix and Classification Report.
5. Explain how the program works and compare these two classification models.
Make you follow all of them so you don't lose any grade points because of that. Feel free to contact me for any questions you may have.
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