Explained Visually personal blog
Principal Component Analysis Explained Visually (2015)
Principal component analysis (PCA) is a technique used to emphasize variation and bring out strong patterns in a dataset. It's often used to make data easy to explore and visualize.
- Points
- 315
- HN comments
- 104
- Submissions
- 4
- Cited by
- 5 commenters
Math & AlgorithmsAI & Machine Learning2017
On Hacker News
| Submitted | Title on HN | Points | Comments |
|---|---|---|---|
| May 23, 2017 | Principal Component Analysis Explained Visually (2015) by espiii | 315 | 25 |
| May 2, 2021 | Principal Component Analysis Explained Visually by xk3 | 213 | 44 |
| Feb 12, 2015 | Principal component analysis explained visually by vicapow | 187 | 22 |
| Oct 29, 2022 | Principal Component Analysis explained visually (2015) by spking | 176 | 13 |
Cited in comments
Linked from 6 Hacker News comments by 5 different people, from Sep 2015 to Oct 2019.
Most recent:
