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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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? ...
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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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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 ...
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Iterative Reweighted Least Squares in python

I am trying to manually implement the irls logistic regression (Chapter 4.3.3 in Bishop - Pattern Recognition And Machine Learning) in python. For updating the weights, I am using $w' = w-(\Phi^TR\...
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Linear Discriminant - Least Squares Classification Bishop 4.1.3

Pls. refer section 4.1.3 in Pattern Recognition - Bishop: "Least squares for Classification": In a 2 class Linear Discriminat system, we classified vector $\mathbf{x}$ as $\mathcal{C}_1$ if ...
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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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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 ...
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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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How to devise multicategory classifiers employing linear discriminant functions?

We might reduce the problem to $c$ two-class problems, where the $i^{th}$ problem is solved by a linear discriminant function that separates points assigned to $w_i$ from those not assigned to $w_1$. ...