Given multivariate data split into several subsamples (classes) the analysis finds linear combinations of variables, called discriminant functions, which discriminate between classes and are uncorrelated. The functions are applied then to assign old or new observations to the classes. Discriminant ...
3
votes
2answers
496 views
Linear discriminant analysis and Bayes rule
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 ...
3
votes
1answer
211 views
What do “real values” refer to in supervised classification?
I'm using supervised classification algorithms from mlpy to classify things into two groups for a question-answering system. I don't really know how these algorithms work, but they seem to be doing ...
2
votes
3answers
250 views
Does PCA followed by LDA make sense?
This is a question about classification. I am a neuroscience student with little experience of classification methods and I'd be grateful for any advice about the best way to implement a linear ...
8
votes
1answer
687 views
Cluster Analysis followed by Discriminant Analysis
What is the rationale, if any, to use Discriminant Analysis (DA) on the results of a clustering algorithm like k-means, as I see it from time to time in the literature (essentially on clinical ...
6
votes
2answers
603 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 ...
4
votes
1answer
410 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 ...
5
votes
1answer
218 views
Classifying clusters using discriminant analysis
Suppose I've data for 100 individuals for 5 variables, say Var1, Var2,...Var5. I run the cluster analysis using these 5 variables on these 100 rows & got 3 clusters. Now, I want to differentiate ...
4
votes
3answers
1k views
What is the relationship between regression and linear discriminant analysis?
Is their a relationship between regression and linear discriminant analysis? What are their similarities and differences? Does it make any difference for two classes and more than two classes?
3
votes
1answer
85 views
Is discriminant analysis supervised learning?
Is linear discriminant analysis, specifically Linear Programming Discriminant Analysis (LPDA), supervised learning? Can you provide a valid reference that states so if possible.
My study supervisor ...
3
votes
1answer
261 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 ...
2
votes
1answer
123 views
Fisher discrimination power of a variable and 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 ...
2
votes
2answers
191 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 ...
