Timeline for Dealing with very small and unbalanced data
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jun 23, 2022 at 17:15 | comment | added | dipetkov | Forecasting implies taking the time dimension and order of episode into account. It's not immediately obvious how you'll make a forecasting argument from a classification model. | |
| Jun 22, 2022 at 23:55 | comment | added | Jonathan | It's not really anything that will be used, it is to demonstrate that it could be possible to forecast the popularity of an episode by using some features extracted from scripts/video | |
| Jun 22, 2022 at 23:53 | comment | added | dipetkov | I'm not sure I understand what problem you are trying to solve. Is this series going to have more seasons? If the series is concluded, then why are you building a classification model? | |
| Jun 22, 2022 at 23:48 | comment | added | Jonathan | @dipetkov Thank you for your interest. I have the data about each existing episode of a tv series, 58 episodes | |
| Jun 22, 2022 at 23:45 | comment | added | dipetkov | Do you have data about one single TV series? In other words, what is the population of TV series that you are studying? | |
| Jun 22, 2022 at 10:54 | vote | accept | Jonathan | ||
| Jun 22, 2022 at 7:19 | answer | added | dx2-66 | timeline score: 3 | |
| Jun 21, 2022 at 23:15 | comment | added | Frank Harrell | This will require a large amount of background reading as you have violated a whole variety of statistical principles. Sorry to not have good news. Check out RMS and fharrell.com/post/classification and note that the minimum sample size for data splitting to work well as a validation method is on the order of n=20,000. You're too subject to "the luck of the split" and are using methods that are harmed by imbalance. Good methods are not hurt by imbalance except for having a lower effective sample size that makes standard errors larger. | |
| Jun 21, 2022 at 22:20 | history | asked | Jonathan | CC BY-SA 4.0 |