Nearest Neighbour Classification: K-means Clustering- MATLAB Assignment Help

Internal Code:TV711

MATLAB Assignment Help:

Task: Assignment Description Wine recognition data is given. Its number of features are: class 1: 59, class 2: 71, class 3: 48. NOTE: 1st dimension out of 15 identifies training and test split (1-training, 2-test). 2 nd dimension is class identifier (1-3). Q1. Distance Metrics Perform nearest neighbour classification experiments according to standard practices in pattern recognition. Use classification error as a fraction of incorrectly classified test points to compare different metrics from the course. Q2. K-means clustering Employ K-means to reduce the complexity of nearest neighbour classifier and compare the performance for different distance metrics. Q3. Neural Network Using Matlab Neural Network toolbox create a network, train and test with the wine data. I would be requiring the matlab code and images for all 3 questions Assignment Description Wine recognition data is given. Its number of features are: class 1: 59, class 2: 71, class 3: 48. NOTE: 1st dimension out of 15 identifies training and test split (1-training, 2-test). 2 nd dimension is class identifier (1-3). Neural Network Using Matlab Neural Network toolbox create a network, train and test with the wine data.