Timeline for How to predict one variable depending upon two other variable in Random Forest?
Current License: CC BY-SA 4.0
5 events
| when toggle format | what | by | license | comment | |
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| Jan 3, 2019 at 8:39 | history | edited | Meghann Mears | CC BY-SA 4.0 |
Corrected description of method
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| Jan 2, 2019 at 0:16 | comment | added | Scholar | @MeghannMears Small correction, random forest uses a different random subset of variables for every split in a tree, not one subset of the for the entire tree. | |
| Dec 7, 2018 at 13:13 | comment | added | Meghann Mears | @PSK0007 It's difficult to judge whether this is high without knowing your dataset (e.g. the order of magnitude of the response variable, whether there are outliers in the reponse variable whose influence might be reduced by transformation, whether the predictors actually do have any predictive value at all). Assuming that it is genuinely larger than realistically expected, have you ensured that you've run enough trees to reach convergence? This might provide some guidance for that. | |
| Dec 6, 2018 at 23:57 | comment | added | PSK0007 | I have tried this but it is giving me a huge Mean Square Residuals : 143703.1, and I think that is wrong, is there anything which I can do? | |
| Dec 6, 2018 at 13:12 | history | answered | Meghann Mears | CC BY-SA 4.0 |