Linear discriminant analysis is also known as canonical discriminant analysis or simply discriminant analysis. Tao Li Shenghuo Zhu and Mitsunori Ogihara.
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Let all the classes have an identical variant ie.
. Three classifiers namely K-nearest neighbor linear discriminant analysis and multi-layer perceptron were used to identify the four emotions of joy happiness anger and sadness and encouraging classification results were achieved. LDA or Linear Discriminant Analysis can be computed in R using the lda function of the package MASS. Method of implementing LDA in R.
For multivariate analysis the value of p is greater than 1. For univariate analysis the value of p is 1 or identical covariance matrices ie. If we want to separate the wines by cultivar the wines come from three different cultivars so the number of groups G is 3 and the number of variables is 13 13 chemicals concentrations.
Linear discriminant analysis frequently achieves good performances in the tasks of face and object recognition even though the assumptions of common covariance matrix among groups and normality are often violated Duda et al 2001 Tao Li et al 2006.
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