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Linear discriminant analysis
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Linear discriminant analysis
Linear discriminant analysis (LDA) is a generalization of Fisher's linear discriminant, a method used in statistics, pattern recognition and machine learning to find a linear combination of features that characterizes or separates two or more classes of objects or events.The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.
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License: Creative Commons Attribution-Share Alike 3.0 (CC-BY-SA-3.0)
Author-Info: The original uploader was Bletchley at English Wikipedia
=======Image-Copyright-Info========
-Video is targeted to blind users
Attribution:
Article text available under CC-BY-SA
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Linear discriminant analysis
Linear discriminant analysis (LDA) is a generalization of Fisher's linear discriminant, a method used in statistics, pattern recognition and machine learning to find a linear combination of features that characterizes or separates two or more classes of objects or events.The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.
=======Image-Copyright-Info========
License: Creative Commons Attribution-Share Alike 3.0 (CC-BY-SA-3.0)
Author-Info: The original uploader was Bletchley at English Wikipedia
=======Image-Copyright-Info========
-Video is targeted to blind users
Attribution:
Article text available under CC-BY-SA
image source in video