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2. [30 marks] (K-Nearest Neighbors) Please show the detailed process of using K- Nearest Neighbor classifier to predict the test instance X= (Speed 5.20, Weight 500) is qualified or not, by setting k= 1, 3, and 5, respectively (20 points). = = Before using KNN classifier, please use Min-max normalization (KNN.pdf page 17) to preprocess the attribute values and plot the preprocessed training data set on a 2d plane (Speed - X axis and Weight - Y axis, the instances of class no are labeled by - and the instances of class yes are labeled by + in the plot) (10 points). Qualified ID 1 2 no no 3 no 4. no 5 no 6 no 7 no 8 no 9 no Speed 2.50 3.75 2.25 3.25 2.75 4.50 3.50 3.00 4.00 4.25 2.00 5.00 8.25 5.75 4.75 5.50 5.25 7.00 7.50 7.25 Weight 600 800 550 825 750 500 525 325 400 375 200 250 850 875 625 675 950 425 800 575 10 11 12 13 no no no no 14 15 yes yes yes 16 yes yes 17 18 19 20 yes yes