Timeline for Outlier detection in out-sample data for the purpose of classification
Current License: CC BY-SA 3.0
4 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 22, 2014 at 7:31 | comment | added | LionelB | If you believe that 30% is too high, then it might be that your rule for outlier detection is too stringent. Relax your rule (changing n in your formula). | |
| Aug 20, 2014 at 8:48 | vote | accept | user2991243 | ||
| Aug 20, 2014 at 8:48 | comment | added | user2991243 | Thank you for your answer. I have second paragraph problem. When I insert new database to my model, the number of outliers is so high (about 30%). How can I solve this? | |
| Aug 20, 2014 at 8:33 | history | answered | LionelB | CC BY-SA 3.0 |