product cost function
51Multidimensional scaling — (MDS) is a set of related statistical techniques often used in information visualization for exploring similarities or dissimilarities in data. MDS is a special case of ordination. An MDS algorithm starts with a matrix of item–item similarities,… …
52Natural monopoly — A monopoly describes a situation where all (or most) sales in a market are undertaken by a single firm. A natural monopoly by contrast is a condition on the cost technology of an industry whereby it is most efficient (involving the lowest long… …
53Isocost — In economics an isocost line represents a combination of inputs which all cost the same amount. Although similar to the budget constraint in consumer theory, the use of the isocost pertains to cost minimization in production, as opposed to… …
54Density of states — Condensed matter physics Phases · Phase tr …
55Matrix chain multiplication — is an optimization problem that can be solved using dynamic programming. Given a sequence of matrices, we want to find the most efficient way to multiply these matrices together. The problem is not actually to perform the multiplications, but… …
56Importance sampling — In statistics, importance sampling is a general technique for estimating the properties of a particular distribution, while only having samples generated from a different distribution rather than the distribution of interest. Depending on the… …
57Economic order quantity — is that level of inventory that minimizes the total of inventory holding cost and ordering cost. The framework used to determine this order quantity is also known as Wilson EOQ Model. The model was developed by F. W. Harris in 1913. But still R.… …
58Veganism — Veganism …
59Multiuser DOS — Company / developer Digital Research, Inc. OS family CP/M Working state Current Source model Closed source Latest stable release V7.22 R18 / 2004 …
60Support vector machine — Support vector machines (SVMs) are a set of related supervised learning methods used for classification and regression. Viewing input data as two sets of vectors in an n dimensional space, an SVM will construct a separating hyperplane in that… …
