Timeline for Clarification for $\beta = {\{\beta_{10},\beta_1}\} $ when fitting logistic regression and the number of classes is k=2
Current License: CC BY-SA 4.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Nov 1, 2020 at 23:08 | comment | added | EA Lehn | please can you help me with this question stats.stackexchange.com/questions/494532/parameters-of-lda | |
| Nov 1, 2020 at 18:11 | vote | accept | EA Lehn | ||
| Nov 1, 2020 at 15:55 | comment | added | nwaldo | You can have more than 8 features - the 10 does not mean Ten. If you have a look on page 119, the authors state that a model with K classes is specified in terms of $K-1$ logit odds - each with their own set of parameters. In your example $K=2$, meaning their is only 1 set. The 1 in $\beta_{10}$ corresponds to this first and only set, while the 0 corresponds to the intercept. | |
| Nov 1, 2020 at 9:48 | comment | added | EA Lehn | Please meaning you can't use th logistics regression when you have 8 or less features. This is because we can't get $ \beta_{10} $ | |
| Nov 1, 2020 at 3:46 | history | answered | nwaldo | CC BY-SA 4.0 |