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Additionally, SEMMA is designed to help the users of the SAS Enterprise Miner software. Therefore, applying it outside Enterprise Miner may be ambiguous. [3] However, in order to complete the "Sampling" phase of SEMMA a deep understanding of the business aspects would have to be a requirement in order to do effective sampling.
Input–output planning was never adopted because the material balance system had become entrenched in the Soviet economy, and input–output planning was shunned for ideological reasons. As a result, the benefits of consistent and detailed planning through input–output analysis were never realized in the Soviet-type economies .
Material input per unit of service (MIPS) is an economic concept, originally developed at the Wuppertal Institute, Germany in the 1990s. The MIPS concept can be used to measure eco-efficiency of a product or service and applied in all scales from a single product to complex systems.
This is a typing short cut for linking to South African Navy ship articles named in the format "SAS President Kruger (F150)". Since Ship names are italicized in article text, linking to them in the usual manner means typing everything twice, such as [[SAS President Kruger (F150)|SAS ''President Kruger'' (F150)]].
A functional specification (also, functional spec, specs, functional specifications document (FSD), functional requirements specification) in systems engineering and software development is a document that specifies the functions that a system or component must perform (often part of a requirements specification) (ISO/IEC/IEEE 24765-2010).
Wire-grid Cobb–Douglas production surface with isoquants A two-input Cobb–Douglas production function with isoquants. In economics and econometrics, the Cobb–Douglas production function is a particular functional form of the production function, widely used to represent the technological relationship between the amounts of two or more inputs (particularly physical capital and labor) and ...
Database design is the organization of data according to a database model.The designer determines what data must be stored and how the data elements interrelate. With this information, they can begin to fit the data to the database model. [1]
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]