Vector Norms in Machine Learning

All norm functions originate from a standard equation of Norm, known as the p-norm. For different values of the parameter p (p should be a real number greater than or equal to 1), we obtain a different norm function. This takes an n-dimensional vector x and raises each element to its p-th power. Then, we sum all the obtained elements and take the p-th root to get the p-norm of the vector, also known as its magnitude. Now, with different values of the parameter p, we will obtain a different norm function.