Supervised Model-based Classification Algorithm: Difference between revisions

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=== 2014 ===
=== 2014 ===
* (Wikipedia, 2014) &rArr; http://en.wikipedia.org/wiki/Statistical_classification Retrieved:2014-11-19.
* (Wikipedia, 2014) &rArr; http://en.wikipedia.org/wiki/Statistical_classification Retrieved:2014-11-19.
** … An algorithm that implements classification, especially in a concrete implementation, is known as a <B>[[Pattern recognition|classifier]]</B>. The term "classifier" sometimes also refers to the mathematical [[function (mathematics)|function]], implemented by a classification algorithm, that maps input data to a category.        <P> Terminology across fields is quite varied. In [[statistics]], where classification is often done with [[logistic regression]] or a similar procedure, the properties of observations are termed [[explanatory variable]]s (or [[independent variable]]s, regressors, etc.), and the categories to be predicted are known as outcomes, which are considered to be possible values of the [[dependent variable]]. In [[machine learning]], the observations are often known as ''instances'', the explanatory variables are termed ''features'' (grouped into a [[feature vector]]), and the possible categories to be predicted are ''classes''. There is also some argumentover whether classification methods that do not involve a [[statistical model]] can be considered "statistical". Other fields may use different terminology: e.g. in [[community ecology]], the term "classification" normally refers to [[cluster analysis]], i.e. a type of [[unsupervised learning]], rather than the supervised learning described in [[this article]].
** … An algorithm that implements classification, especially in a concrete implementation, is known as a <B>[[Pattern recognition|classifier]]</B>. The term "classifier" sometimes also refers to the mathematical [[function (mathematics)|function]], implemented by a classification algorithm, that maps input data to a category.        <P>       Terminology across fields is quite varied. In [[statistics]], where classification is often done with [[logistic regression]] or a similar procedure, the properties of observations are termed [[explanatory variable]]s (or [[independent variable]]s, regressors, etc.), and the categories to be predicted are known as outcomes, which are considered to be possible values of the [[dependent variable]]. In [[machine learning]], the observations are often known as ''instances'', the explanatory variables are termed ''features'' (grouped into a [[feature vector]]), and the possible categories to be predicted are ''classes''. There is also some argumentover whether classification methods that do not involve a [[statistical model]] can be considered "statistical". Other fields may use different terminology: e.g. in [[community ecology]], the term "classification" normally refers to [[cluster analysis]], i.e. a type of [[unsupervised learning]], rather than the supervised learning described in [[this article]].


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Revision as of 15:32, 19 August 2021

A supervised model-based classification algorithm is a supervised classification algorithm that is a supervised model-based learning algorithm.



References

2014