Timeline for Can a Linear Regression Model (with no higher order coefficients) over-fit?
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| May 21, 2022 at 1:23 | vote | accept | Batool | ||
| Dec 29, 2020 at 2:34 | vote | accept | Batool | ||
| May 20, 2022 at 19:36 | |||||
| Dec 25, 2020 at 1:42 | comment | added | Dave | I posted a simulation I like over at the Data Science Stack: datascience.stackexchange.com/a/79994/73930. | |
| Dec 25, 2020 at 0:50 | answer | added | Detelina Stoyanova | timeline score: 2 | |
| Jan 31, 2020 at 16:01 | comment | added | user137795 | I removed my accepted answer due to a helpful downvote to inspire a better answer, @gwg. But for someone may find a compact answer useful, I place it here as comment: Assuming the real model is: $y_i = \beta_0 + \beta_1 X_{i1} + \epsilon_i$ but you add a factor $X_{2i}$ which is not related the $y_i$ to model and fit the new model $y_i = \beta_0 + \beta_1 X_{i1} + \beta_2 X_{i2} + \epsilon_i$ In general, you will get a $\hat{\beta_2} \neq 0$ , then if you run the model to predict something including factor $X_{i2}$ , you will suffer over-fit. | |
| Apr 13, 2017 at 12:44 | history | edited | CommunityBot |
replaced http://stats.stackexchange.com/ with https://stats.stackexchange.com/
|
|
| Apr 11, 2017 at 15:23 | vote | accept | Batool | ||
| Dec 29, 2020 at 2:34 | |||||
| Apr 11, 2017 at 15:17 | history | edited | Batool | CC BY-SA 3.0 |
edited title
|
| Apr 11, 2017 at 4:23 | answer | added | user137795 | timeline score: 4 | |
| Apr 11, 2017 at 3:22 | history | asked | Batool | CC BY-SA 3.0 |