30k views

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 ...
• 861
43k views

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 ...
• 477
12k views

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. ...
• 1,974
17k views

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 ...
• 261
40k views

In R, I use lda function from library MASS to do classification. As I understand LDA, input $... • 3,623 14 votes 1 answer 10k views Bayesian and Fisher's approaches to linear discriminant analysis I know 2 approaches to do LDA, the Bayesian approach and the Fisher's approach. Suppose we have the data$(x,y)$, where$x$is the$p$-dimensional predictor and$y$is the dependent variable of$K$... • 3,623 10 votes 1 answer 4k views Sources' seeming disagreement on linear, quadratic and Fisher's discriminant analysis I'm studying discriminant analysis, but I'm having a difficult time reconciling several different explanations. I believe I must be missing something, because I've never encountered this (seeming) ... • 1,846 3 votes 2 answers 5k views Why is LDA considered to be a classifier? I am new to machine learning and I was reading about dimensional reduction algorithms like LDA(linear discriminant analysis) and PCA. Currently I am using LDA to find the optimal dimensions that ... • 171 8 votes 1 answer 4k views Relation of Mahalanobis Distance to Log Likelihood The Wikipedia entry on Mahalanobis Distance contains this note: Another intuitive description of Mahalanobis distance is that it is square root of the negative log likelihood. That is, the ... • 255 4 votes 2 answers 2k views Can you use discriminant analysis to classify new observations into categories generated by a previous$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 ...
• 3,875
4k views

What Is the Loss (Objective) Function for Linear Discriminant Analysis (LDA)?

As many algorithms can be viewed as optimization problems through the Loss function, I was wondering if such a loss function existed for LDA (linear classification). And if yes, what would it be ? I ...
• 385
5k views

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 ...
2k views

How does Fisher LDA work?

Intuitively, how does Fisher LDA work? From this Linear discriminant analysis and Bayes rule: classification I completely understood the Bayesian approach but I'm not able to relate it to the Fisher'...
• 101
1 vote
3k views

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 ...
• 757
2k views

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 ...
• 429

15 30 50 per page