Timeline for machine learning model with 50% chance to be deterministic
Current License: CC BY-SA 3.0
4 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Nov 23, 2014 at 13:35 | comment | added | rolando2 | I like the first 1/2 of the answer. "looking at all your data to decide what features to include": if this approach were taken, then your point about cross-validation wouldn't apply, because this would not even be cross-validation. It would defeat the purpose of cross-validation. | |
| Nov 17, 2013 at 20:02 | comment | added | PascalVKooten | It seems more likely to separate the data perhaps. The actual goal at this moment is to predict the price the product was offered for (though the goal is arbitrary; it's just a fun thing). | |
| Nov 17, 2013 at 19:59 | comment | added | PascalVKooten | What I meant was that this method doesn't predict 249 which is really close to 250 (the actual value), but there is around a 50% chance the error will be 0. I'm having doubts whether having it as a feature (where perhaps the estimates will just be used in 100% of the cases to make some prediction, even though the other 50% time it might be about some version number or something instead of the actual price mentioned) | |
| Nov 17, 2013 at 18:33 | history | answered | alto | CC BY-SA 3.0 |