normm
Normm is a term sometimes used informally to refer to the family of Lp norms on a vector space, where the parameter m labels the order of the norm. In this usage, for a vector x in Rn, the norm is defined as ||x||m = (sum_i |x_i|^m)^(1/m). When m is an element of [1, ∞), this function is a genuine norm, and it is widely known as the Lp norm with p = m. As m increases, the norm becomes more sensitive to the largest coordinate; as m decreases toward 1, it emphasizes a larger number of coordinates.
Special cases are well known: m = 2 yields the Euclidean norm, m = 1 gives the Manhattan
Normm/Lp norms have broad applications in mathematics, statistics, and machine learning. They are used to measure
Although normm is not a formal, universally standardized term, it is commonly understood as shorthand for the