Linked Questions

1 vote
0 answers
811 views

Understanding the math behind linear discriminant analysis [duplicate]

I am trying to understand Eigenfaces Vs. Fisherfaces: Recognition Using Class Specific Linear Projection paper. It uses PCA and further uses LDA for dimensionality reduction. I have read about ...
Naman's user avatar
  • 123
0 votes
0 answers
266 views

Interpreting LDA graph in R [duplicate]

I am trying to carry out linear discriminant analysis and plot the results graphically: ...
The Pointer's user avatar
  • 2,096
137 votes
7 answers
29k views

Is there an intuitive interpretation of $A^TA$ for a data matrix $A$?

For a given data matrix $A$ (with variables in columns and data points in rows), it seems like $A^TA$ plays an important role in statistics. For example, it is an important part of the analytical ...
Alec's user avatar
  • 2,395
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
  • 861
34 votes
2 answers
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 ...
Andrius's user avatar
  • 477
22 votes
2 answers
9k 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 ...
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
  • 6,615
27 votes
2 answers
12k views

Why is Python's scikit-learn LDA not working correctly and how does it compute LDA via SVD?

I was using the Linear Discriminant Analysis (LDA) from the scikit-learn machine learning library (Python) for dimensionality reduction and was a little bit curious ...
user avatar
22 votes
1 answer
11k views

How is MANOVA related to LDA?

In several places I saw a claim that MANOVA is like ANOVA plus linear discriminant analysis (LDA), but it was always made in a hand-waving sort of way. I would like to know what exactly it is supposed ...
amoeba's user avatar
  • 106k
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
12 votes
3 answers
29k views

Can the scaling values in a linear discriminant analysis (LDA) be used to plot explanatory variables on the linear discriminants?

Using a biplot of values obtained through principal component analysis, it is possible to explore the explanatory variables that make up each principle component. Is this also possible with Linear ...
Etienne Low-Décarie's user avatar
19 votes
3 answers
40k views

What are "coefficients of linear discriminants" in LDA?

In R, I use lda function from library MASS to do classification. As I understand LDA, input $...
avocado's user avatar
  • 3,633
12 votes
2 answers
18k views

Standardizing features when using LDA as a pre-processing step

If a multi-class Linear Discriminant Analysis (or I also read Multiple Discriminant Analysis sometimes) is used for dimensionality reduction (or transformation after dimensionality reduction via PCA), ...
user avatar
10 votes
1 answer
12k views

Proportion of explained variance in PCA and LDA

I have some basic questions regarding PCA (principal component analysis) and LDA (linear discriminant analysis): In PCA there is a way to calculate the proportion of variance explained. Is it also ...
wrek's user avatar
  • 111
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
  • 1,846

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