Assuming that the SVM is used here to map the feature vectors 
and 
with their corresponding class labels 
and 1, the training label vector y can be created as follows:
and with their corresponding class labels and 1, the training label vector y can be created as follows:M_minus = size(E_minus, 1);
M_plus = size(E_plus, 1);
% Create the label vector
labels_minus = -1 * ones(M_minus, 1);
labels_plus = 1 * ones(M_plus, 1);
% Combine the labels
y = [labels_minus; labels_plus];
% Combine the feature vectors
features = [E_minus; E_plus];
% Train SVM model
SVMModel = fitcsvm(features, y);
Using the attached script "SVMTest.m" you can test the code and check out the accuracy and predictions of the SVM.
