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What is the relationship between regression and linear discriminant analysis (LDA)?

Is there a relationship between regression and linear discriminant analysis (LDA)? What are their similarities and differences? Does it make any difference if there are two classes or more than two ...
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Three versions of discriminant analysis: differences and how to use them

Can anybody explain differences and give specific examples how to use these three analyses? LDA - Linear Discriminant Analysis FDA - Fisher's Discriminant Analysis QDA - Quadratic Discriminant ...
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Discriminant analysis vs logistic regression

I found some pros of discriminant analysis and I've got questions about them. So: When the classes are well-separated, the parameter estimates for logistic regression are surprisingly unstable. ...
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Algebra of LDA. Fisher discrimination power of a variable and Linear Discriminant Analysis

Apparently, the Fisher analysis aims at simultaneously maximising the between-class separation, while minimising the within-class dispersion. A useful measure of the discrimination power of a ...
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In R, I use lda function from library MASS to do classification. As I understand LDA, input $... 1answer 7k views Bayesian and Fisher's approaches to linear discriminant analysis I know 2 approaches to do LDA, the Bayesian approach and the Fisher's approach. Suppose we have the data$(x,y)$, where$x$is the$p$-dimensional predictor and$y$is the dependent variable of$K$... 1answer 2k views Sources' seeming disagreement on linear, quadratic and Fisher's discriminant analysis I'm studying discriminant analysis, but I'm having a difficult time reconciling several different explanations. I believe I must be missing something, because I've never encountered this (seeming) ... 2answers 2k views Why is LDA considered to be a classifier? I am new to machine learning and I was reading about dimensional reduction algorithms like LDA(linear discriminant analysis) and PCA. Currently I am using LDA to find the optimal dimensions that ... 1answer 1k views Relation of Mahalanobis Distance to Log Likelihood The Wikipedia entry on Mahalanobis Distance contains this note: Another intuitive description of Mahalanobis distance is that it is square root of the negative log likelihood. That is, the ... 2answers 1k views Can you use discriminant analysis to classify new observations into categories generated by a previous$k\$-means clustering?

After doing k-means clustering on a set of observations, I would like to construct a discriminant function so as to classify new observations into the categories I found after k-means. Is this at all ...
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How is the tied covariance matrix enforced in Linear Discriminant Analysis?

In the general case of Gaussian Discriminant Analysis, we learn the Gaussian parameters for each class. I understand that if each class distribution has the same covariance matrix, then the learned ...
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Interpreting LD1 and LD2 in lda in R

I'm conducting an experiment in R. I am using the rattle library that contains a sample of the wine related data. Within this ...
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A question on discriminant analysis- Linear discriminant function

Above is part of an examination paper. I am not sure how to understand this SAS output. Especially what is there in the last table which looks to me like two discriminant functions. Can someone help ...