Timeline for Model optimization causes overfitting
Current License: CC BY-SA 4.0
13 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 28, 2023 at 21:49 | comment | added | user17818805 | I did'nt get that 'Once you've the initial parameters you can refine the parameter search around the initial values - nothing wrong with that and that can even be coded (automated). The only minor issue is reducing the size of the training split (60% is a bit low). That can cause issues in which case the split is 70:20:10, i.e. 10 for validation'. | |
| Aug 28, 2023 at 21:11 | history | edited | M__♦ | CC BY-SA 4.0 |
added 238 characters in body
|
| Aug 28, 2023 at 20:58 | history | edited | M__♦ | CC BY-SA 4.0 |
added 760 characters in body
|
| Aug 28, 2023 at 20:56 | comment | added | user17818805 | I understood you the least lost data will infer my model. I can't improve my accuracy, I've changed the model inputs leaving only the OTUs, I've tried the PCA but to no avail. | |
| Aug 28, 2023 at 20:50 | comment | added | M__♦ | @user17818805 answered above below the last ------- | |
| Aug 28, 2023 at 20:38 | comment | added | user17818805 | Thanks for your reply, but I tried what you suggested but it gave me lower accuracy values. | |
| Aug 25, 2023 at 17:04 | history | edited | M__♦ | CC BY-SA 4.0 |
added 21 characters in body
|
| Aug 25, 2023 at 16:59 | history | edited | M__♦ | CC BY-SA 4.0 |
added 21 characters in body
|
| Aug 25, 2023 at 13:09 | history | edited | M__♦ | CC BY-SA 4.0 |
added 189 characters in body
|
| Aug 25, 2023 at 10:52 | history | edited | M__♦ | CC BY-SA 4.0 |
added 83 characters in body
|
| Aug 25, 2023 at 10:47 | history | edited | M__♦ | CC BY-SA 4.0 |
added 83 characters in body
|
| Aug 25, 2023 at 10:40 | history | edited | M__♦ | CC BY-SA 4.0 |
added 166 characters in body
|
| Aug 25, 2023 at 10:34 | history | answered | M__♦ | CC BY-SA 4.0 |