Linear Discriminative Model Algorithm: Difference between revisions
Jump to navigation
Jump to search
(Created page with "A Linear Discriminative Model Algorithm is a discriminative model algorithm that ... * <B>See:</B> Linear Discriminant Analysis Algorithm. ---- ---- == References...") |
m (Text replacement - "]]↵↵----↵" to "]]. ---- ") |
||
(7 intermediate revisions by 2 users not shown) | |||
Line 1: | Line 1: | ||
A [[Linear Discriminative Model Algorithm]] is a [[discriminative model algorithm]] that ... | A [[Linear Discriminative Model Algorithm]] is a [[discriminative model algorithm]] that ... | ||
* <B>See:</B> [[Linear Discriminant Analysis Algorithm]]. | * <B>See:</B> [[Linear Discriminant Analysis Algorithm]]. | ||
---- | ---- | ||
---- | ---- | ||
== References == | == References == | ||
=== 2016 === | === 2016 === | ||
* http://wnzhang.net/teaching/cs420/slides/2-linear-model.pdf | * http://wnzhang.net/teaching/cs420/slides/2-linear-model.pdf | ||
** QUOTE: [[Linear Discriminative Models]] | ** QUOTE: [[Linear Discriminative Model Algorithm|Linear Discriminative Models]]. | ||
*** [[Discriminative model]] | *** [[Discriminative model]]. | ||
**** [[modeling the dependence of unobserved variables on observed ones]] | **** [[modeling the dependence of unobserved variables on observed ones]]. | ||
**** also called [[conditional models]]. | **** also called [[conditional models]]. | ||
**** [[Deterministic]]: <math>y=f_\theta(x)</math> | **** [[Deterministic]]: <math>y=f_\theta(x)</math> | ||
**** [[Probabilistic]]: <math>y=p_\theta(y\mid x)</math> | **** [[Probabilistic]]: <math>y=p_\theta(y\mid x)</math> | ||
*** [[Linear regression model]] | *** [[Linear regression model]]. | ||
---- | ---- | ||
__NOTOC__ | __NOTOC__ | ||
[[Category:Concept]] |
Latest revision as of 03:50, 8 May 2024
A Linear Discriminative Model Algorithm is a discriminative model algorithm that ...
References
2016
- http://wnzhang.net/teaching/cs420/slides/2-linear-model.pdf
- QUOTE: Linear Discriminative Models.
- Discriminative model.
- modeling the dependence of unobserved variables on observed ones.
- also called conditional models.
- Deterministic: [math]\displaystyle{ y=f_\theta(x) }[/math]
- Probabilistic: [math]\displaystyle{ y=p_\theta(y\mid x) }[/math]
- Linear regression model.
- Discriminative model.
- QUOTE: Linear Discriminative Models.