View source for Parametric Statistical Modeling Algorithm

A [[Parametric Statistical Modeling Algorithm]] is a [[Learning Algorithm]] that assumes knowledge of the [[Dataset]]'s underlying [[Distribution Function]].
* <B>AKA:</B> [[Parametric Statistical Modeling Algorithm|Parametric Statistical Algorithm]], [[Parametric Statistical Modeling Algorithm|Parametric Learning Algorithm]].
* <B>Context</U>:</B>
** It can be:
*** a [[Parametric Classification Algorithm]].
*** a [[Parametric Regression Algorithm]].
* <B>Example(s):</B> 
** a [[Parametric Classification Algorithm]].
*** [[Linear Classification Algorithm]].
*** [[Logistic Regression Classification Algorithm]].
*** [[Support Vector Machine]] [[Learning Algorithm]].
** a [[Parametric Regression Algorithm]].
*** [[Linear Regression Algorithm]].
*** [[Generalized Linear Model]] [[Learning Algorithm]].
*** [[Mixture Model]] [[Learning Algorithm]].
*** [[Probabilistic Graphical Model]] [[Learning Algorithm]].
*** [[Hidden Markov Model]] [[Learning Algorithm]].
** …
* <B>Counter-Example(s):</B> 
** a [[Nonparametric Statistical Modeling Algorithm]].
* <B>See</U>:</B> [[Parametric]].

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== References ==

=== 2009 ===
* ([[2009_StatisticalMachineLearningCourse10-702|Lafferty & Wasserman, 2009]]) ⇒ [[John D. Lafferty]], and [[Larry Wasserman]]. ([[2009]]). “[http://www.cs.cmu.edu/~10702/ Statistical Machine Learning - Course: 10-702]." Spring 2009, Carnegie Mellon Institute.
** '''Parametric methods:''' Linear Regression, Model Selection, Generalized Linear Models, Mixture Models, Classification (linear, logistic, support vector machines), Graphical Models, Structured Prediction, Hidden Markov Models.

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[[Category:Concept]]