Timeline for How to get the training error and the validation error using Classify function with SVM
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
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| Jun 9, 2016 at 10:10 | comment | added | Ronald Monson | I agree the improved performance is due to some validation but whether or not it is due to the validation specified in the option or else due to the inbuilt cross-validation still seems questionable to me - see, for example, these runs. | |
| Feb 17, 2016 at 8:39 | comment | added | Sjoerd C. de Vries | @ronald You often see that a trained classifier has a lower performance on an out-of-sample test. This is often due to overfitting. In this case performance of the out-of-sample fraction is equal to the training sample, which is quite good and which I feel is due to the presence of the validation sample. | |
| Feb 17, 2016 at 2:52 | comment | added | Ronald Monson | "The validation set has been used to good effect" - is that the case here? I find it has no effect | |
| Feb 9, 2016 at 21:57 | history | edited | Sjoerd C. de Vries | CC BY-SA 3.0 |
added 562 characters in body
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| Feb 9, 2016 at 21:45 | vote | accept | BetterEnglish | ||
| Feb 17, 2016 at 11:58 | |||||
| Feb 9, 2016 at 21:34 | history | answered | Sjoerd C. de Vries | CC BY-SA 3.0 |