# 70 search results for "discriminant"

## Quadratic Discriminant Analysis of Several Groups

January 12, 2017
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Quadratic discriminant analysis for classification is a modification of linear discriminant analysis that does not assume equal covariance matrices amongst the groups . Similar to LDA for several groups, quadratic discriminant analysis of several groups classification seeks to find the group that maximizes the quadratic classification function and assign the... The post Quadratic Discriminant Analysis of Several Groups...

## Quadratic Discriminant Analysis of Two Groups

December 29, 2016
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As mentioned in the post on classification with linear discriminant analysis, LDA assumes the groups in question have equal covariance matrices . Therefore, often when the groups do not have equal covariance matrices, observations are frequently assigned to groups with large variances on the diagonal of its corresponding covariance matrix... The post Quadratic Discriminant Analysis of Two Groups...

## Classification with Linear Discriminant Analysis

December 23, 2016
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Classification with linear discriminant analysis is a common approach to predicting class membership of observations. A previous post explored the descriptive aspect of linear discriminant analysis with data collected on two groups of beetles. In this post, we will use the discriminant functions found in the first post to classify... The post Classification with Linear Discriminant Analysis appeared...

## Discriminant Analysis of Several Groups

December 15, 2016
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Discriminant analysis is also applicable in the case of more than two groups. In the first post on discriminant analysis, there was only one linear discriminant function as the number of linear discriminant functions is , where is the number of dependent variables and is the number of groups. In... The post Discriminant Analysis of Several Groups appeared...

## Discriminant Analysis for Group Separation in R

November 17, 2016
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The term ‘discriminant analysis’ is often used interchangeably to represent two different objectives. These objectives of discriminant analysis are: Description of group separation. Linear combinations of variables, known as discriminant functions, of the dependent variables that maximize the separation between the groups are used to identify the relative contribution of... The post Discriminant Analysis for Group Separation in...

## Supervised Classification, discriminant analysis

March 3, 2015
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Another popular technique for classification (or at least, which used to be popular) is the (linear) discriminant analysis, introduced by Ronald Fisher in 1936. Consider the same dataset as in our previous post > clr1 <- c(rgb(1,0,0,1),rgb(0,0,1,1)) > x <- c(.4,.55,.65,.9,.1,.35,.5,.15,.2,.85) > y <- c(.85,.95,.8,.87,.5,.55,.5,.2,.1,.3) > z <- c(1,1,1,1,1,0,0,1,0,0) > df <- data.frame(x,y,z) > plot(x,y,pch=19,cex=2,col=clr1) The main interest of...

## Analyse discriminante linéaire ou Regression logistique

July 10, 2013
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Supposons que l'on dispose d'iris de Paris (en population >100khabts) et qu'on veuille pouvoir les classer selon leurs caractéristiques sociodémos : Population taux de chômage Etudiants CSP etc... Une fois, les iris classés, on se demande si l'on peut transporter cette typologie à une autre grande ville (Lyon) par exemple : Il faudrait alors pouvoir utiliser un modèle d'affectation des iris selon leurs caractéristiques respectives...

## A Brief Look at Mixture Discriminant Analysis

July 2, 2013
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Lately, I have been working with finite mixture models for my postdoctoral work on data-driven automated gating. Given that I had barely scratched the surface with mixture models in the classroom, I am becoming increasingly comfortable with them. With this in mind, I wanted to explore their application to classification because there are times when a single class is clearly made up of...

## My Intro to Multiple Classification with Random Forests, Conditional Inference Trees, and Linear Discriminant Analysis

December 27, 2012
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After the work I did for my last post, I wanted to practice doing multiple classification.  I first thought of using the famous iris dataset, but felt that was a little boring.  Ideally, I wanted to look for a practice … Continue reading →

## An example of linear discriminant analysis

January 8, 2011
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The following example was shown in an advanced statistics seminar held in tel aviv. The material for the presentation comes from C.M Bishop’s book : Pattern Recognition and Machine Learning by Springer(2006). One way of separating 2 categories using linear sub spaces of the input space (e.g. planes for 3D inputs, lines for 2D inputs, [&hellip