Algorithms: Difference between revisions
| Line 26: | Line 26: | ||
Algorithm: | Algorithm: | ||
===O( | ===<math>O(n \log n)</math> Algorithms=== | ||
====Merge Sort==== | ====Merge Sort==== | ||
====Heap Sort==== | ====Heap Sort==== | ||
Revision as of 17:59, 11 December 2019
Algorithms
Sorting
Given: compare(a,b) to compare 2 numbers. Goal: Sort a list of numbers from smallest to largest.
\(\displaystyle O(n^2)\) Algorithms
Bubble Sort
Insertion Sort
Basic Idea:
- Maintain a subarray which is always sorted
Algorithm:
- Grab a number from the unsorted portion and insert it into the sorted portion
- Repeat until no more numbers are in the unsorted subarray
Selection Sort
Basic Idea:
- Maintain a subarray which is always sorted.
- Every number in the sorted subarray will be smaller than the smallest number in the unsorted subarray.
Algorithm:
- Find the smallest number in the unsorted portion and insert it into the sorted portion
- Repeat until no more numbers are in the unsorted subarray.
Quicksort
Basic Idea:
- Divide an conquer.
- Very fast. Average case O(nlogn).
- Good for multithreaded systems.
Algorithm:
\(\displaystyle O(n \log n)\) Algorithms
Merge Sort
Heap Sort
Linear Algorithms
Counting Sort
Radix Sort
Selection
Given: compare(a,b) to compare 2 numbers. A number k. Goal: Return the k'th largest number.