Machine Learning, Single Layer Perceptron, Neural Networks, Matlab.
Y; dL_dW = (X' * dL_dZ) / size(X, 1); dL_db = mean(dL_dZ, 1); % Update the weights and biases W = W - learning_rate * dL_dW; b = b - learning_rate * dL_db; end 6. Evaluate the trained model: [~, y_pred] = max(S, [], 2); accuracy = sum(y_pred == y) / numel(y); fprintf('Training set accuracy: