Timeline for How do various statistical techniques (regression, PCA, etc) scale with sample size and dimension?
Current License: CC BY-SA 3.0
8 events
| when toggle format | what | by | license | comment | |
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| Aug 16, 2014 at 10:39 | comment | added | Has QUIT--Anony-Mousse | In many cases, the original literature will discuss complexity. But often theoretical complexity is useless. QuickSort has a worst-case of O(n^2), but often is the fastest - faster than HeapSort, which has worst case O(n log n). If you do a little research, you will find out complexity results for many algorithms - if known. E.g. PCA being O(n d^3), k-means being O(n k i d) etc. | |
| Aug 14, 2014 at 17:28 | answer | added | StasK | timeline score: 5 | |
| Aug 8, 2014 at 0:25 | answer | added | shadowtalker | timeline score: 5 | |
| Aug 6, 2014 at 0:23 | comment | added | shadowtalker | This is a good question. A lot of statistics books talk about the theoretical aspects of high-dimensional data and not the computational aspects. | |
| Aug 5, 2014 at 20:24 | answer | added | damienfrancois | timeline score: 6 | |
| Aug 5, 2014 at 18:46 | history | edited | Bridgeburners | CC BY-SA 3.0 |
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| Aug 5, 2014 at 18:39 | review | First posts | |||
| Aug 7, 2014 at 23:44 | |||||
| Aug 5, 2014 at 18:36 | history | asked | Bridgeburners | CC BY-SA 3.0 |