정렬 알고리즘

수학노트
둘러보기로 가기 검색하러 가기

노트

  1. A Sorting Algorithm is used to rearrange a given array or list elements according to a comparison operator on the elements.[1]
  2. Sorting algorithm specifies the way to arrange data in a particular order.[2]
  3. Sorting algorithms may require some extra space for comparison and temporary storage of few data elements.[2]
  4. However, in some sorting algorithms, the program requires space which is more than or equal to the elements being sorted.[2]
  5. A sorting algorithm is said to be adaptive, if it takes advantage of already 'sorted' elements in the list that is to be sorted.[2]
  6. Sorting algorithms are ways to organize an array of items from smallest to largest.[3]
  7. The main advantage of this sorting algorithm is that it is more efficient than a regular insertion sort.[3]
  8. As a result, programmers can quickly and easily implement this sorting algorithm.[3]
  9. Quicksort is one of the most efficient sorting algorithms, and this makes of it one of the most used as well.[3]
  10. In computer science, a sorting algorithm is an algorithm that puts elements of a list in a certain order.[4]
  11. Comparison-based sorting algorithms need at least Ω( log ) comparisons for most inputs.[4]
  12. In particular, some sorting algorithms are "in-place".[4]
  13. Exchange sorts include bubble sort and quicksort.[4]
  14. These pages show 8 different sorting algorithms on 4 different initial conditions.[5]
  15. If you have your own types, it may get cumbersome implementing a separate sorting algorithm for each one.[6]
  16. Based on Recursion or Non-Recursion Some sorting algorithms, such as Quick Sort , use recursive techniques to sort the input.[7]
  17. Other sorting algorithms, such as Selection Sort or Insertion Sort , use non-recursive techniques.[7]
  18. Finally, some sorting algorithm, such as Merge Sort , make use of both recursive as well as non-recursive techniques to sort the input.[7]
  19. A simple way to solve this problem would be to use another sorting algorithm such as Merge sort, Heap Sort or Quick Sort.[7]
  20. In this article we'll have a look at popular sorting algorithms, understand how they work and code them in Python.[8]
  21. This popular sorting algorithm, like the Insertion and Selection sorts, segments the list into sorted and unsorted parts.[8]
  22. This divide and conquer algorithm is the most often used sorting algorithm covered in this article.[8]
  23. Sorting algorithms gives us many ways to order our data.[8]
  24. Bubble sort steps through the list and compares adjacent pairs of elements.[9]
  25. Quick sort is also a divide and conquer algorithm like merge sort.[9]
  26. Pick the right sorting algorithm, and your program can run quickly.[10]
  27. Pick the wrong sorting algorithm, and your program may seem unbearably slow to the user.[10]
  28. A sorting algorithm will put items in a list into an order, such as alphabetical or numerical order.[11]
  29. Some sorting algorithms have certain additional options.[12]
  30. At the top, you will see the list of commonly taught sorting algorithms in Computer Science classes.[12]
  31. The first six algorithms are comparison-based sorting algorithms while the last two are not.[12]
  32. The middle three algorithms are recursive sorting algorithms while the rest are usually implemented iteratively.[12]
  33. Merge Sort - Merge sort (also commonly spelled mergesort) is an efficient, general-purpose, comparison-based sorting algorithm.[13]
  34. Selection Sort - selection sort is a sorting algorithm, specifically an in-place comparison sort.[13]
  35. heapsort is a comparison-based sorting algorithm.[13]
  36. When implemented well, it can be about two or three times faster than its main competitors, merge sort and heapsort.[13]
  37. Sorting algorithms take lists of items as input data, perform specific operations on those lists and deliver ordered arrays as output.[14]
  38. A sorting algorithm is an algorithm that puts elements of a list in a certain order.[15]
  39. For typical sorting algorithms, a good behavior is ( log ) and a bad behavior is ( ).[15]
  40. In particular, some sorting algorithms are "in place".[15]
  41. Stable sorting algorithms maintain the relative order of records with equal keys (i.e., values).[15]
  42. Most sorting algorithms work by comparing the data being sorted.[16]
  43. Sorting algorithms are usually judged by their efficiency.[16]
  44. Some algorithms, such as quick sort, perform exceptionally well for some inputs, but horribly for others.[16]
  45. A third criterion is stability -- does the sort preserve the order of keys with equal values?[16]
  46. A number of such sorting algorithms exist which are optimized, but their execution time is still to be optimized.[17]
  47. It is a stable sorting algorithm and is very efficient to handle big numbers.[17]
  48. While talking about quick sort at an instant, in our mind, there comes the concept of pivot element.[17]
  49. It is an unstable sorting algorithm built on the binary search tree (BST).[17]
  50. If you've used the native sort methods in Python or NodeJS, you've interfaced with Timsort.[18]
  51. However, Timsort's merge sort strategy is a little different from traditional sorting algorithms.[18]
  52. Like searching, the efficiency of a sorting algorithm is related to the number of items being processed.[19]
  53. The total number of comparisons will be the most common way to measure a sort procedure.[19]
  54. The universally-acclaimed worst sorting algorithm is Bogosort, sometimes called Monkey Sort or Random Sort, for reasons we’ll see shortly.[20]
  55. Merge sort is a good choice if you want a stable sorting algorithm.[21]
  56. is a good choice if you want a stable sorting algorithm.[21]
  57. Some Sorting Algorithm is stable by nature like Insertion Sort, Merge Sort and Bubble Sort etc.[22]
  58. Sorting Algorithm is not stable like Quick Sort, Heap Sort etc.[22]
  59. In-Place, Sorting Algorithm updates input only through replacement or swapping of elements.[22]
  60. Bubble sort, insertion sort, and selection sort are in-place sorting algorithms.[22]
  61. Python's sort happens to implement an excellent sorting algorithm that was invented for Python itself.[23]
  62. The stability of a sorting algorithm represents the ability of the algorithm to maintain the original order of equal elements after sorting.[24]
  63. In terms of memory usage, it will perform slightly worse than the usual sorting algorithm.[24]
  64. Timsort is one of the fastest sorting algorithms for real world problems.[24]
  65. All comparison-based sorting algorithms have a complexity lower bound of nlogn.[25]
  66. The algorithm that accepts a new element while the sorting process is going on, that algorithm is called the online sorting algorithm.[25]
  67. Understanding the sorting algorithms are the best way to learn problem solving and complexity analysis in the algorithms.[25]
  68. Whether it be it a list, array, or any collection, the very first problem we face is choosing the right sorting algorithm.[26]
  69. The case for a learned sorting algorithm, Kristo, Vaidya, et al.[27]
  70. The base version of Learned Sort is an out-of-place sort, meaning that it copies the sorted elements into a new destination array.[27]
  71. The first phase of learned sort is a cascading Bucket Sort.[27]

소스

  1. ↑ Sorting Algorithms
  2. ↑ 2.0 2.1 2.2 2.3 Sorting Techniques
  3. ↑ 3.0 3.1 3.2 3.3 Sorting Algorithms
  4. ↑ 4.0 4.1 4.2 4.3 Sorting algorithm
  5. ↑ Sorting Algorithms Animations
  6. ↑ Sorting Algorithms in Java
  7. ↑ 7.0 7.1 7.2 7.3 Sorting Algorithms Explained with Examples in Python, Java, and C++
  8. ↑ 8.0 8.1 8.2 8.3 Sorting Algorithms in Python
  9. ↑ 9.0 9.1 A tour of the top 5 sorting algorithms with Python code
  10. ↑ 10.0 10.1 Essential Programming | Sorting Algorithms
  11. ↑ Why do we need sorting algorithms?
  12. ↑ 12.0 12.1 12.2 12.3 Sorting (Bubble, Selection, Insertion, Merge, Quick, Counting, Radix)
  13. ↑ 13.0 13.1 13.2 13.3 CS Sorting Algorithm
  14. ↑ What is sorting algorithm?
  15. ↑ 15.0 15.1 15.2 15.3 CS241: Data Structures & Algorithms II
  16. ↑ 16.0 16.1 16.2 16.3 Sorting Algorithms Compared
  17. ↑ 17.0 17.1 17.2 17.3 SA Sorting: A Novel Sorting Technique for Large-Scale Data
  18. ↑ 18.0 18.1 The most important sorting algorithm you need to know
  19. ↑ 19.0 19.1 6.6. Sorting — Problem Solving with Algorithms and Data Structures
  20. ↑ Baeldung on Computer Science
  21. ↑ 21.0 21.1 Sorting algorithm reference, for coding interviews and computer science classes
  22. ↑ 22.0 22.1 22.2 22.3 DAA Stable Sorting
  23. ↑ sorting algorithm
  24. ↑ 24.0 24.1 24.2 Timsort and Introsort: Swift's Sorting Algorithms
  25. ↑ 25.0 25.1 25.2 Comparison of Sorting Algorithms
  26. ↑ Best Sorting Algorithm
  27. ↑ 27.0 27.1 27.2 The case for a learned sorting algorithm

메타데이터

위키데이터

Spacy 패턴 목록

  • [{'LOWER': 'sorting'}, {'LEMMA': 'algorithm'}]
  • [{'LEMMA': 'asc'}]
  • [{'LEMMA': 'desc'}]
  • [{'LEMMA': 'sort'}]
원본 주소 "https://wiki.mathnt.net/index.php?title=정렬_알고리즘&oldid=51424"