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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?
aan's user avatar
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31 votes
4 answers
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 ...
zca0's user avatar
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22 votes
2 answers
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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 ...
jerry_sjtu's user avatar
27 votes
1 answer
16k 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. ...
Victor's user avatar
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16 votes
1 answer
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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 ...
category's user avatar
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15 votes
2 answers
22k 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 ...
zca0's user avatar
  • 861
14 votes
2 answers
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 ...
highBandWidth's user avatar
9 votes
1 answer
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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 ...
garak's user avatar
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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 $K$ ...
avocado's user avatar
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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) ...
Zenit's user avatar
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9 votes
1 answer
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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 ...
ttnphns's user avatar
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1 vote
1 answer
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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 ...
Daniel's user avatar
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0 votes
0 answers
4k 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 ...
Ébe Isaac's user avatar
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2 votes
1 answer
1k 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: ...
Omar Wagih's user avatar
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0 answers
810 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 ...
Annalise Azzopardi's user avatar

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