Timeline for Detecting spammers with artificially generated target class
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Nov 19, 2017 at 18:58 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Oct 20, 2017 at 18:35 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| S Sep 20, 2017 at 17:43 | history | suggested | Mephy | CC BY-SA 3.0 |
More descriptive title
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| Sep 20, 2017 at 14:13 | answer | added | Mephy | timeline score: 2 | |
| Sep 20, 2017 at 14:09 | review | Suggested edits | |||
| S Sep 20, 2017 at 17:43 | |||||
| Sep 20, 2017 at 12:38 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Aug 21, 2017 at 12:28 | answer | added | CalZ | timeline score: 0 | |
| Aug 20, 2017 at 20:16 | comment | added | Paul | Welcome to real world data science, where the points are all made up and the scores don't really matter. I have been in the situation of being given data to model, only to find out that the target was artificial. Seriously, I the only way that do machine learning here is get accurate target data. | |
| Aug 20, 2017 at 19:37 | review | First posts | |||
| Aug 20, 2017 at 19:40 | |||||
| Aug 20, 2017 at 19:35 | history | asked | Fernando Contreras | CC BY-SA 3.0 |