Machine Learning, Logistics Regression, Logistic Regression Model, Logistic Regression, Regularization.
(1-y)’*log(1-h))/m + p; % calculate grads grad = (x’*(h — y)+lambda*theta1)/m; end Conclusion I trust that gives you a good overview of why we apply regularisation. You can go onto the next article where go through a good example.