# Tagged Questions

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 ...

765 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 ...
287 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 ...
253 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 ...
321 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 ...
917 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 ...
2k views

### What is the relationship between regression and linear discriminant analysis?

Is there a relationship between regression and linear discriminant analysis? What are their similarities and differences? Does it make any difference if there are two classes or more than two classes? ...
512 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 ...
579 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 ...
844 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 ...
115 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 ...
614 views

### Are Fisher's linear discriminant and logistic regression classifier related?

I have some experience with both FLD and LR for classification. On most data sets, I get very similar results, which raises the question - are FLD and LR related in some why? An idea, for example, ...
263 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 ...
114 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 ...
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 ...