• Corpus ID: 8370473

Fisher Linear Discriminant Analysis

@inproceedings{Li2014FisherLD,
  title={Fisher Linear Discriminant Analysis},
  author={Cheng Li},
  year={2014}
}
Fisher Linear Discriminant Analysis (also called Linear Discriminant Analysis(LDA)) are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which 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. LDA is closely related to PCA, for both of them are based on linear, i.e. matrix… 

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