Linked Questions

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0answers
77 views

Is Linear Discriminate Analysis (LDA) and Fisher Discriminant Analysis (FDA) same meaning? [duplicate]

Is Linear Discriminate Analysis (LDA) and Fisher Discriminant Analysis (FDA) same meaning? And also Fisher Criterion (FC)? Do these three terms interchangeably, having the same meaning?
26
votes
4answers
23k 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 ...
21
votes
2answers
7k views

How does linear discriminant analysis reduce the dimensions?

There are words from "The Elements of Statistical Learning" on page 91: The K centroids in p-dimensional input space span at most K-1 dimensional subspace, and if p is much larger than K, this ...
24
votes
1answer
13k views

How LDA, a classification technique, also serves as dimensionality reduction technique like PCA

In this article , the author links linear discriminant analysis (LDA) to principal component analysis (PCA). With my limited knowledge, I am not able to follow how LDA can be somewhat similar to PCA. ...
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1answer
13k 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 ...
12
votes
2answers
17k views

Linear discriminant analysis and Bayes rule: classification

What is the relation between Linear discriminant analysis and Bayes rule? I understand that LDA is used in classification by trying to minimize the ratio of within group variance and between group ...
13
votes
2answers
5k views

Why are Gaussian “discriminant” analysis models called so?

Gaussian discriminant analysis models learn $P(x|y)$ and then apply Bayes rule to evaluate $$P(y|x) = \frac{P(x|y)P_{prior}(y)}{\Sigma_{g \in Y} P(x|g) P_{prior}(g) }.$$ Hence, they are generative ...
11
votes
1answer
9k 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 $K$ ...
9
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1answer
6k views

Multi class LDA vs 2 class LDA

The problem of designing a multi-class classifier using LDA can be expressed as a 2 class problem(one vs everything else) or a multi-class problem. Why is it that in certain cases Multi-class LDA ...
10
votes
1answer
3k 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) ...
8
votes
1answer
2k views

Plotting a discriminant as line on scatterplot

Given a data scatterplot I can plot the data's principal components on it, as axes tiled with points which are principal components scores. You can see an example plot with the cloud (consisting of 2 ...
0
votes
0answers
3k views

What is the difference between MDA and LDA and how is it applied in SciKit-learn?

According to this paper, Canonical Discriminant Analysis (CDA) is basically Principal Component Analysis (PCA) followed by Multiple Discriminant Analysis (MDA). I am assuming that MDA is just ...
1
vote
1answer
989 views

Under which circumstances does LDA achieve a higher classification accuracy than QDA?

Since some weeks, I pursue the question "Under which circumstances will LDA achieve a higher classification accuracy than QDA using the same training and test set as well as the same prior ...
2
votes
1answer
775 views

Linear discriminant analysis posterior not giving expected values in R

I have two normal distributions fg and bg with mean (mu) and standard deviations (sd) as follows: ...
0
votes
0answers
498 views

Homogeneity of Covariance Matrix and LDA

I have been using Iris data for a classification problem in SPSS. The Box's M-test is used to check the assumption whether all co-variance matrices are equal or not. Now since the p.value for Iris ...

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