Linear Discriminant Analysis (LDA) Modeling System: Difference between revisions
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A [[Linear Discriminant Analysis (LDA) Modeling System]] is a [[model-based supervised classification system]] that implements a [[linear discriminant analysis algorithm]] to solve a [[linear discriminant analysis task]]. | A [[Linear Discriminant Analysis (LDA) Modeling System]] is a [[model-based supervised classification system]] that implements a [[linear discriminant analysis algorithm]] to solve a [[linear discriminant analysis task]]. | ||
* <B>See:<B> [[discriminant_analysis.LinearDiscriminantAnalysis]]. | * <B>See:</B> [[discriminant_analysis.LinearDiscriminantAnalysis]]. | ||
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== References == | == References == | ||
=== 2009 === | === 2009 === | ||
* https://scikit-learn.org/stable/modules/lda_qda.html#lda-qda | * https://scikit-learn.org/stable/modules/lda_qda.html#lda-qda | ||
** QUOTE: ][[Linear Discriminant Analysis]] ([[discriminant_analysis.LinearDiscriminantAnalysis]]) and [[Quadratic Discriminant Analysis]] ([[discriminant_analysis.QuadraticDiscriminantAnalysis]]) are two classic [[supervised classification algorithm|classifier]]s, with, as their names suggest, a [[linear]] and a [[quadratic decision surface]], respectively. <P> These classifiers are attractive because they have closed-form solutions that can be easily computed, are inherently multiclass, have proven to work well in practice, and have no hyperparameters to tune. | ** QUOTE: ][[Linear Discriminant Analysis]] ([[discriminant_analysis.LinearDiscriminantAnalysis]]) and [[Quadratic Discriminant Analysis]] ([[discriminant_analysis.QuadraticDiscriminantAnalysis]]) are two classic [[supervised classification algorithm|classifier]]s, with, as their names suggest, a [[linear]] and a [[quadratic decision surface]], respectively. <P> These classifiers are attractive because they have closed-form solutions that can be easily computed, are inherently multiclass, have proven to work well in practice, and have no hyperparameters to tune. <P> <HTML><IMG SRC=https://scikit-learn.org/stable/_images/sphx_glr_plot_lda_qda_001.png></HTML> | ||
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[[Category:Concept]] | |||
Latest revision as of 18:52, 17 September 2021
A Linear Discriminant Analysis (LDA) Modeling System is a model-based supervised classification system that implements a linear discriminant analysis algorithm to solve a linear discriminant analysis task.
References
2009
- https://scikit-learn.org/stable/modules/lda_qda.html#lda-qda
- QUOTE: ]Linear Discriminant Analysis (discriminant_analysis.LinearDiscriminantAnalysis) and Quadratic Discriminant Analysis (discriminant_analysis.QuadraticDiscriminantAnalysis) are two classic classifiers, with, as their names suggest, a linear and a quadratic decision surface, respectively.
These classifiers are attractive because they have closed-form solutions that can be easily computed, are inherently multiclass, have proven to work well in practice, and have no hyperparameters to tune.
- QUOTE: ]Linear Discriminant Analysis (discriminant_analysis.LinearDiscriminantAnalysis) and Quadratic Discriminant Analysis (discriminant_analysis.QuadraticDiscriminantAnalysis) are two classic classifiers, with, as their names suggest, a linear and a quadratic decision surface, respectively.