init commit

MC_NDCC_matlab/NDCC.m

@@ -0,0 +1,39 @@
+%{
+NORMALLY DISTRIBUTED CLUSTERS is a data generator. 
+It generates a series of random centers for multivariate
+normal distributions. NDC randomly generates a fraction
+of data for each center, i.e. what fraction of data points
+will come from this center. NDC randomly generates a 
+separating plane. Based on this plane, classes for are 
+chosen for each center. NDC then randomly generates the 
+points from the distributions. NDC can increase 
+inseparability by increasng variances of distributions.
+A measure of "true" separability is obtained by looking 
+at how many points end up on the wrong side of the 
+separating plane. All values are taken as integers 
+for simplicity.
+%}
+
+
+centers_list = [100, 300, 500];
+n_samples  = input('Enter the number of samples:\n');
+n_features = input('Enter the number of features:\n');
+n_classes  = input('Enter the number of classes:\n');
+
+
+% Generating center matrix based on centers_list and number of features
+centers_matrix = get_centers_mat(centers_list, n_features);
+n_centers = 2*length(centers_list)*n_features;
+
+% The same number of randomly chosen centers will dedicate to each class
+class_locations = class_center_locations(n_classes, n_centers);
+
+% Deciding randomly that how many samples should be in each class_locations
+ss = sample_spliter(n_samples, n_classes, n_centers);
+
+%Generating dataset 
+ds = generate_dataset(centers_matrix, ss,class_locations, n_features);
+
+%Saving the dataset as a csv file in current directory
+writematrix(ds, 'dataset.csv');
+