A simple object recognition system encodes objects using 3-element feature vectors. 5 objects from 3 different classes are encoded as follows: Feature vector Class (0.5, -0.4,0.5) (1) (-0.6, -0.2,0.1) (1) (0.3,0.3, 0.4) (2) (-0.6, -0.1, -0.5) (3) (-0.8,0.4,0.5) (2) A new object of an unknown class has a feature vector (-0.1, -0.3, 0.3). Using the Euclidean distance as the similarity measure, determine the classification of the new object using: i) a nearest mean classifier ii) a nearest neighbor classifier i) a k-nearest neighbor classifier, with k=3 ANSWER: The minimal distance computed by the nearest mean classifier over classes: (to 2 decimal places) The minimal distance computed by the nearest neighbor classifier over objects: (to 2 decimal places) The predicted class of the k-nearest neighbor classifier