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study:algorithms:o-notation

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study:algorithms:o-notation [2013/04/28 13:41] okie 새로 만듦 |
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4. When is such an analysis useful? | 4. When is such an analysis useful? | ||

- | * ease of programming : though O(n^2) < O(n^3), | + | * ease of programming : though O(n^2) < O(n^3), we may prefer O(n^3) algorithm |

- | we may prefer O(n^3) algorithm | + | * if it has a small constant of proportionality it is easy to program |

- | if it has a small constant of proportionality | + | |

- | it is easy to program | + | |

- | | + | |

- | * In some cases, the features avaliable | + | |

- | on a machine make an algorithm especally fast | + | |

- | eg) parallel hardware | + | |

- | | + | |

- | * We often do the worst case analysis because it's easy | + | |

- | eg) Quicksort = O(n^2) | + | |

+ | * In some cases, the features avaliable on a machine make an algorithm especally fast. eg) parallel hardware | ||

+ | * We often do the worst case analysis because it's easy. eg) Quicksort = O(n^2) | ||

* We can not compare two algorithm of the same order | * We can not compare two algorithm of the same order | ||

study/algorithms/o-notation.txt · Last modified: 2019/02/04 14:26 (external edit)

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