output vector - significado y definición. Qué es output vector
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Qué (quién) es output vector - definición

A PROPERTY DESCRIBING RUN-TIME COMPLEXITY OF ALGORITHMS
Output sensitivity; Output-sensitivity

Kernel methods for vector output         
User:Clynnepstein/Kernel methods for vector output
Kernel methods are a well-established tool to analyze the relationship between input data and the corresponding output of a function. Kernels encapsulate the properties of functions in a computationally efficient way and allow algorithms to easily swap functions of varying complexity.
Output (economics)         
QUANTITY OF GOODS OR SERVICES PRODUCED IN A GIVEN TIME PERIOD, BY A FIRM, INDUSTRY, OR COUNTRY, WHETHER CONSUMED OR USED FOR FURTHER PRODUCTION
Netput; Economic output
Output in economics is the "quantity of goods or services produced in a given time period, by a firm, industry, or country",Alan Deardorff. output, Deardorff asspoo's Glossary of International Economics.
Output device         
  • A recording setup with two monitor speakers
  • upright=0.6
  • [[Colossal Cave Adventure]] being played on a [[VT100]] terminal
  • upright=0.8
  • A pair of [[computer speaker]]s and a [[subwoofer]] used in a desktop environment
  • An [[LCD monitor]] in use
  • An LED projector
  • Output interfaces on the rear of a graphics card
TYPE OF COMPUTER HARDWARE DEVICE THAT TRANSMITS INFORMATION FROM THE COMPUTER TO THE USER
Graphical output device; Output devices; List of output devices; Output hardware
An output device is any piece of computer hardware equipment which converts information into a human-perceptible form or, historically, into a physical machine-readable form for use with other non-computerized equipment. It can be text, graphics, tactile, audio, or video.

Wikipedia

Output-sensitive algorithm

In computer science, an output-sensitive algorithm is an algorithm whose running time depends on the size of the output, instead of, or in addition to, the size of the input. For certain problems where the output size varies widely, for example from linear in the size of the input to quadratic in the size of the input, analyses that take the output size explicitly into account can produce better runtime bounds that differentiate algorithms that would otherwise have identical asymptotic complexity.