Linear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant...

stage based on backpropagation. Linear discriminant analysis (LDA) is a generalization of Fisher's linear discriminant, a method used in statistics, pattern...

{class}}|{\vec {x}})}. Examples of such algorithms include: Linear Discriminant Analysis (LDA)—assumes Gaussian conditional density models Naive Bayes...

Fisher discriminant analysis (KFD), also known as generalized discriminant analysis and kernel discriminant analysis, is a kernelized version of linear discriminant...

of linear subspace learning methods such as principal component analysis (PCA), independent component analysis (ICA), linear discriminant analysis (LDA)...

complex separating surfaces. Quadratic discriminant analysis (QDA) is closely related to linear discriminant analysis (LDA), where it is assumed that the...

multiple measurements in taxonomic problems as an example of linear discriminant analysis. It is sometimes called Anderson's Iris data set because Edgar...

machines, and linear discriminant analysis), as well as in various other models, such as principal component analysis and factor analysis. In many of these...

algorithms are: Support-vector machines Linear regression Logistic regression Naive Bayes Linear discriminant analysis Decision trees K-nearest neighbor algorithm...

Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data...