Timeline for Why gradient boosting/random forest generate "unstable" feature importance?
Current License: CC BY-SA 3.0
3 events
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| May 15, 2017 at 19:39 | comment | added | LookIntoEast | "bootstrap the results and estimate their variability." Could you explain more explicitly? Basically say run this 100 times and calculate the average importance for each feature? | |
| May 15, 2017 at 17:21 | comment | added | Matthew Drury | A consequence for me has always been: if you are trying to draw any inferences from those importances, you must bootstrap the results and estimate their variability. | |
| May 15, 2017 at 17:15 | history | answered | Firebug | CC BY-SA 3.0 |