For the following training data set (three classes, each class has 10 samples and each sample has two features). Assume equal a priori probabilities, Gausian density functios, and∑i =∑, for i=1,2..
Class W1 Class W2
X1 X2 X1 X2
3.406 4.439 -4.306 4.967
3.811 4.893 -4.581 3.527
4.395 3.351 -3.606 3.334
5.340 2.770 -3.640 4.041
4.238 4.093 -2.899 4.127
4.249 3.562 -5.044 3.889
2.917 4.121 -3.501 4.047
4.992 4.851 -2.967 2.224
3.556 3.414 -3.466 4.475
4.437 3.178 -3.131 2.235
Predict the class label for the following test samples using
i. Euclidean distance
ii. Mahalanobis distance
iii. CITY block DISTANCE
X1 X2
4.7583 1.432
-4.020 -2.817
Class W1 Class W2
X1 X2 X1 X2
3.406 4.439 -4.306 4.967
3.811 4.893 -4.581 3.527
4.395 3.351 -3.606 3.334
5.340 2.770 -3.640 4.041
4.238 4.093 -2.899 4.127
4.249 3.562 -5.044 3.889
2.917 4.121 -3.501 4.047
4.992 4.851 -2.967 2.224
3.556 3.414 -3.466 4.475
4.437 3.178 -3.131 2.235
Predict the class label for the following test samples using
i. Euclidean distance
ii. Mahalanobis distance
iii. CITY block DISTANCE
X1 X2
4.7583 1.432
-4.020 -2.817