# Questions tagged [discriminant-analysis]

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 analysis is both dimensionality reduction and classification technique.

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### Difference between FDA and LDA

I have asked this question in Mathematics Stackexchange, thought however that it might be more fit for here: I am currently taking a Data-Analysis course and I learned about both the terms LDA (Linear ...
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### Fisher Linear Discriminant

We know that the formula of Fisher Linear Discriminant regarding the weight vector is : My question is does this formula put any constraint on the magnitude of the weight vector w? or the magnitude ...
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### Apply linear Discriminant analysis

Let's say that our feature space is of dimension size = 9. Also, let's say that we apply LDA and we get only one LDA component. If we developed for example the SVM model and test the accuracy with ...
16 views

### Direct Discriminative Pattern Mining for Effective Classification - implementation

I'm looking for any actual working code implementation of the DDPMiner algorithm mentioned in the Direct Discriminative Pattern Mining for Effective Classification article form 2008 I'm having real ...
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### Help with DDP Mining algorithm for Effective Classification of data sets from 2 groups

I'm trying to implement the DDPmine algorithm from this article as part of some project, and I do not understand where in the algorithm we use the Class Label of each transaction? We have transactions ...
31 views

### Linear discriminant analysis in R: how to choose the most suitable model?

The data set vaso in the robustbase library summarizes the vasoconstriction (or not) of subjects’ fingers along with their breathing volumes and rates. ...
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### Naive Bayes Classifier - Discriminant Function

To classify my samples, I decided to use Naive Bayes classifier, but I coded it, not used built-in library functions. If I use this equality, I obtain nice classification accuracy: ...
136 views

### Performace of Fischer projection as dimension reduction compared to other LDA methods

How is the performance of Fischer projection compared to other LDA methods of dimension reduction? I thought that Fischer projection was a great method of dimension reduction by maximizing class ...
88 views

### Convert a pdf into a conditional pdf such that mean increases and std dev falls

Let success metric(for some business use case I am working on) be a continuous random variable S. The mean of pdf defined on S indicates the chance of success. Higher the mean more is the chance of ...
47 views

### What is the favored discriminant analysis package in R?

I have been using the LDA package for R, but it is missing quite a few features especially those that can assess the output. Are the any preferred packages that have some of the following? ...
522 views

### Gaussian Discriminant Analysis (GDA) package in R

This stack exchange post - https://stats.stackexchange.com/questions/80507/what-is-a-gaussian-discriminant-analysis-gda - discusses GDA, a machine learning method for classification. I would like to ...
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### Varying results when calculating scatter matrices for LDA

I'm following a Linear Discriminant Analysis tutorial from here for dimensionality reduction. After working through the tutorial (did the PCA part, too), I shortened the code using sklearn modules ...
I am drawing samples from two classes in the two-dimensional Cartesian space, each of which has the same covariance matrix $[2, 0; 0, 2]$. One class has a mean of $[1.5, 1]$ and the other has a mean ...