462CCS-5 Computer Science Department Instructor: Instructor: Dr. Mohamed Ghouse Subject Coordinator: Dr.Monia Iris classification The Iris Dataset (Iris.csv) contains four features (length and width of sepals and petals) of 50 samples of three species of Iris (Iris setosa, Iris virginica, and Iris versicolor). Activity requirements 1. Load the dataset and visualize the characteristics of the dataset 2. Build a k-nearest neighbor classification model 3. Assess the performance of the classifier using Training and test. 4. Using random splitting to train/test many time (10 times or even 100 times), compute the best value of the parameter k (you can choose k that ensures the lowest misclassification error). The misclassification error =1 - classification score(accuracy) K can be chosen in an interval of odd integer from 1 to 50 . This process can be performed by cross validation (ten folders, 1 for test and the remaining nine for training)