Model-based Learning Algorithm: Difference between revisions
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A [[Model-based Learning Algorithm]] is a [[ | A [[Model-based Learning Algorithm]] is a [[learning algorithm]] that can be applied by a [[model-based learning system]] to solve a [[model-based learning task]] (which requires the production of a [[model-based prediction function]]). | ||
* <B | * <B>AKA:</B> [[Supervised Model-based Learning Algorithm]], [[Model-based Learning Algorithm|Model-based Training Algorithm]]. | ||
* <B | * <B>Context</U>:</B> | ||
** It can | ** It can range from being a [[Supervised Model-based Learning Algorithm]] to being an [[Unsupervised Model-based Learning Algorithm]]. | ||
** It can range from being a [[ | ** It can range from being a [[Model-based Classification Algorithm]] to being a [[Model-based Ranking Algorithm]] to being a [[Model-based Estimation Algorithm]]. | ||
** It can range from being a [[Lazy Model-based Learning Algorithm]] to being an [[Eager Model-based Learning Algorithm]]. | |||
** It can range from being a [[Discriminative Learning Algorithm]] to being a [[Generative Learning Algorithm]]. | ** It can range from being a [[Discriminative Learning Algorithm]] to being a [[Generative Learning Algorithm]]. | ||
* <B>Example(s):</B> | |||
* <B | ** a [[Regression Algorithm]], such as a [[least-squares function fitting algorithm]]. | ||
** a [[Regression Algorithm]]. | ** a [[Statistical Modeling Algorithm]], such as s [[Linear Model Learning Algorithm]] or a [[Logistic Regression Model Learning Algorithm]]. | ||
** a [[Statistical Modeling Algorithm]] | ** a [[Decision Tree Learning Algorithm]], such as a [[C4.5 Algorithm]]. | ||
** a [[Discriminative Machine Learning Algorithm]], such as a [[logistic regression]]. | |||
** a [[Neural-Network Learning Algorithm]], such as a [[backprop learning algorithm]]. | |||
** [[ | ** a [[Kernel-based Learning Algorithm]], such as an [[SVM algorithm]]. | ||
** a [[ | ** … | ||
** a [[ | * <B>Counter-Example(s):</B> | ||
** a [[ | |||
* <B | |||
** an [[Instance-based Learning Algorithm]], such as: [[k-Nearest Neighbor Algorithm]]. | ** an [[Instance-based Learning Algorithm]], such as: [[k-Nearest Neighbor Algorithm]]. | ||
** a [[Locally Weighted Regression Algorithm]]. | ** a [[Locally Weighted Regression Algorithm]]. | ||
* <B | * <B>See</U>:</B> [[Unsupervised Learning Algorithm]]. | ||
---- | ---- | ||
---- | ---- | ||
===1993=== | == References == | ||
* (Quinlan, 1993) | |||
=== 1993 === | |||
* ([[Quinlan, 1993]]) ⇒ [[J. Ross Quinlan]]. ([[1993]]). “Combining Instance-based and Model-based Learning.” In: Proceedings of the Tenth International Conference on Machine Learning. | |||
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Latest revision as of 05:19, 28 November 2023
A Model-based Learning Algorithm is a learning algorithm that can be applied by a model-based learning system to solve a model-based learning task (which requires the production of a model-based prediction function).
- AKA: Supervised Model-based Learning Algorithm, Model-based Training Algorithm.
- Context:
- It can range from being a Supervised Model-based Learning Algorithm to being an Unsupervised Model-based Learning Algorithm.
- It can range from being a Model-based Classification Algorithm to being a Model-based Ranking Algorithm to being a Model-based Estimation Algorithm.
- It can range from being a Lazy Model-based Learning Algorithm to being an Eager Model-based Learning Algorithm.
- It can range from being a Discriminative Learning Algorithm to being a Generative Learning Algorithm.
- Example(s):
- a Regression Algorithm, such as a least-squares function fitting algorithm.
- a Statistical Modeling Algorithm, such as s Linear Model Learning Algorithm or a Logistic Regression Model Learning Algorithm.
- a Decision Tree Learning Algorithm, such as a C4.5 Algorithm.
- a Discriminative Machine Learning Algorithm, such as a logistic regression.
- a Neural-Network Learning Algorithm, such as a backprop learning algorithm.
- a Kernel-based Learning Algorithm, such as an SVM algorithm.
- …
- Counter-Example(s):
- See: Unsupervised Learning Algorithm.
References
1993
- (Quinlan, 1993) ⇒ J. Ross Quinlan. (1993). “Combining Instance-based and Model-based Learning.” In: Proceedings of the Tenth International Conference on Machine Learning.