enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Algorithm characterizations - Wikipedia

    en.wikipedia.org/wiki/Algorithm_characterizations

    The following are desirable features of a well-defined algorithm, as discussed in Scheider and Gersting (1995): Unambiguous Operations: an algorithm must have specific, outlined steps. The steps should be exact enough to precisely specify what to do at each step.

  3. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.

  4. Feature selection - Wikipedia

    en.wikipedia.org/wiki/Feature_selection

    This can lead to poor performance [34] when the features are individually useless, but are useful when combined (a pathological case is found when the class is a parity function of the features). Overall the algorithm is more efficient (in terms of the amount of data required) than the theoretically optimal max-dependency selection, yet ...

  5. Feature (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Feature_(machine_learning)

    In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. [1] Choosing informative, discriminating, and independent features is crucial to produce effective algorithms for pattern recognition, classification, and regression tasks.

  6. Algorithmic technique - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_technique

    There are several broadly recognized algorithmic techniques that offer a proven method or process for designing and constructing algorithms. Different techniques may be used depending on the objective, which may include searching, sorting, mathematical optimization, constraint satisfaction, categorization, analysis, and prediction.

  7. Feature (computer vision) - Wikipedia

    en.wikipedia.org/wiki/Feature_(computer_vision)

    Since features are used as the starting point and main primitives for subsequent algorithms, the overall algorithm will often only be as good as its feature detector. Consequently, the desirable property for a feature detector is repeatability : whether or not the same feature will be detected in two or more different images of the same scene.

  8. Algorithm - Wikipedia

    en.wikipedia.org/wiki/Algorithm

    Flowchart of using successive subtractions to find the greatest common divisor of number r and s. In mathematics and computer science, an algorithm (/ ˈ æ l ɡ ə r ɪ ð əm / ⓘ) is a finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation. [1]

  9. Heuristic (computer science) - Wikipedia

    en.wikipedia.org/wiki/Heuristic_(computer_science)

    Instead, the greedy algorithm can be used to give a good but not optimal solution (it is an approximation to the optimal answer) in a reasonably short amount of time. The greedy algorithm heuristic says to pick whatever is currently the best next step regardless of whether that prevents (or even makes impossible) good steps later.