Timeline for Numerical computation of cross entropy in practice
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 11, 2020 at 16:05 | history | edited | Sycorax♦ | CC BY-SA 4.0 | added 55 characters in body |
| Jul 6, 2020 at 19:09 | history | edited | Sycorax♦ | CC BY-SA 4.0 | added 113 characters in body |
| Jul 5, 2020 at 15:32 | history | edited | Sycorax♦ | CC BY-SA 4.0 | added 12 characters in body |
| Jul 5, 2020 at 15:27 | vote | accept | Josh | ||
| Jul 5, 2020 at 15:22 | history | edited | Sycorax♦ | CC BY-SA 4.0 | added 202 characters in body |
| Jul 5, 2020 at 15:20 | comment | added | Sycorax♦ | Yes, $p$ is the label and $q$ is the predicted probability of $y=1$. I've added clarification for the second part of your comment. | |
| Jul 5, 2020 at 15:03 | comment | added | Josh | Thanks Syrocorax! Great suggestions. And just to complete everything here, in addition to what you wrote above, in a classification setting, when using $H(p,q)$ as your loss, you would define $q$ as the probability output of the network, and $p$ as the ground truth labels, and not the other way around, right? (moreover, this should also fully avoid the $\log\; 0 = -\inf$ problem I mentioned, right?) | |
| Jul 5, 2020 at 13:53 | history | edited | Sycorax♦ | CC BY-SA 4.0 | added 738 characters in body |
| Jul 5, 2020 at 13:32 | history | answered | Sycorax♦ | CC BY-SA 4.0 |