2. (25 points) k nearest neighbours (kNN). You will use the data in Tables 3-4 Table 3: Training data for non-clustering algorithms. "Number of teeth" is number of teeth left at the end of the player's career Player Height (cm) |Weight (kg) Number of Teeth Career Fights 201 176 184 182 181 185 186 166 189 109 107 92 104 100 26 28 30 30 32 31 25 28 26 50 10 10 104 83 122 50 100 Table 4: Testing data for non-clustering algorithms. "Number of teeth" is number of teeth left at the end of the player's career Player Height (cm) |Weight (kg) Number of Teeth Career Fights 185 178 187 103 86 29 30 25 100 2. (25 points) k nearest neighbours (kNN). You will use the data in Tables 3-4 Table 3: Training data for non-clustering algorithms. "Number of teeth" is number of teeth left at the end of the player's career Player Height (cm) |Weight (kg) Number of Teeth Career Fights 201 176 184 182 181 185 186 166 189 109 107 92 104 100 26 28 30 30 32 31 25 28 26 50 10 10 104 83 122 50 100 Table 4: Testing data for non-clustering algorithms. "Number of teeth" is number of teeth left at the end of the player's career Player Height (cm) |Weight (kg) Number of Teeth Career Fights 185 178 187 103 86 29 30 25 100