Timeline for Visualizing a large number of continuous variables
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 18, 2017 at 21:59 | answer | added | Tebalo | timeline score: 1 | |
| Aug 28, 2016 at 23:27 | comment | added | Kodiologist | @machinelearningguy Finding multivariate outliers by eye in a dataset this size is out of the question. (I have enough trouble visualizing 3-dimensional space; 2,000-dimensional space is best left to Lovecraft.) If you want multivariate outliers, try these methods. | |
| Aug 28, 2016 at 3:41 | comment | added | GeoMatt22 | If you put all the predictors onto the same "scale" (e.g. standardize or normalize), then you could do histograms of all variables using the same set of bins. Say you have 100 bins, then you could visualize the conditional PDFs of your predictors as two 100 by 2000 grayscale images (one image for each value of the outcome). These could be composited in different ways into a single RGB(A) image if you wish. | |
| Aug 27, 2016 at 23:58 | comment | added | machinelearningguy | @whuber: To look at the distributions of the variables and see if there are any outliers. | |
| Aug 27, 2016 at 22:10 | comment | added | whuber♦ | What would be the objectives of the visualization? | |
| Aug 27, 2016 at 21:46 | history | asked | machinelearningguy | CC BY-SA 3.0 |