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 ...

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How LDA, a classification technique, also serves as dimensionality reduction technique like PCA

In this article , the author links linear discriminant analysis (LDA) to principal component analysis (PCA). With my limited knowledge, I am not able to follow how LDA can be somewhat similar to PCA. ...
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9 views

Structural partition for cross validation

Can the partitioning of data for cross validation be used structurally to assess the transfer ability of an effect of one factor across another factor? A MANOVA performed on multivariate data reveals ...
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1answer
39 views

Fisher Projection vs Linear Discriminant Analysis [closed]

Basically, I am confused between Fisher and LDA. Looking for differences between the two. How is the Fischer projection computed in R?
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1answer
41 views

Difference between within-group and between-group covariance matrices in linear discriminant analysis

Could someone explain to me the difference between within-group covariance matrix and between-group covariance matrix in the context of linear discriminant analysis?
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14 views

Sphering and Centering Data

If I have a bunch of data points that like in p-dimensions, what does it mean if the data is sphered and centered. I never really understood this concept and was wondering if anyone could explain it ...
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17 views

get constant LDA in R from SPSS result [duplicate]

I tried discriminant analysis with lda() in R and in SPSS. data: ...
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20 views

What is correct implementation of LDA (Linear Discriminant Analysis)? [migrated]

I found that the result of LDA in OpenCV is different from other libraries. For example, the input data was ...
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1answer
90 views

Why are discriminant analysis results in R (lda) and SPSS different?: Constant term

I tried discriminant analysis with lda() in R and in SPSS, but the scalings were different, why? N, how to get (Constant) with R like SPSS result? data: ...
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2answers
78 views

Best way to bin continuous data

I have a data frame with 1 vector of integers and 1 as a character factor like so: I have created a linear model that shows a relationship between age and party affiliation. I now want to determine ...
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14 views

Multivariate technique to determine whether an effect is intermediate to two or more other effects?

Let’s say I am looking at soil microbial community structure. I have a multivariate dataset with 20 dependent variables indicating various soil microbial biomarkers in the soil. My treatments include ...
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1answer
43 views

A book on discriminant analysis

Can anyone suggest a good book on discriminant analysis - comprehensible and detailed? (Kendall and Stuart write about the subject too concisely.)
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24 views

LDA scores too big

I'm trying to do dimensionality reduction with linear discriminant analysis (LDA) in MATLAB. I'm using this code to calculate the coefficients. But I'm confused whether (and when) should I center the ...
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24 views

Data sets for which PCA can classify better than LDA (using a very small training set)

Can you provide an example of a dataset where PCA can find better discriminant directions than (LDA) Linear Discriminant Analysis? One example is UCI's wine data set. If you use only 2 observations ...
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34 views

Fisher LDA is a Bayes Classifier?

I've been going over many material in classification algorithms, and it seems that under the constraint that the covariance matrices are the same for a two-class problem then classifying a vector $x$ ...
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12 views

Non-negative Fisher LDA?

Is any one aware of any existing publication on non-negative solution for (Fisher's) linear discriminant analysis?. In particular: $$\text{maximize}_{w\geq0} ~ ...
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45 views

How to quantify performance of Linear Discriminant Analysis (LDA)?

I have implemented Linear Discriminant Analysis (LDA) for dimensionality reduction in C. But I don't know how to quantify performance of the LDA. Could someone help me?
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1answer
35 views

pattern classification when the prior probabilities are not equal

In the case of 2 class classification, the decision boundary occurs when 2 discriminant functions are equal: $$ g_1(x) = g_2(x) $$ $$ g_i(x) = p(x|w_i)P(w_i) $$ $$ p(x|w_i) = ...
3
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1answer
73 views

Supervised dimensionality reduction

I have a data set consisting of 15K labeled samples (of 10 groups). I want to apply dimensionality reduction into 2 dimensions, that would take into consideration the knowledge of the labels. When I ...
0
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1answer
13 views

What metric should be used to compare models when the prediction is a probability of an event occurring?

Let's say that I am trying to predict whether or not it will rain today, and I build a model that gives me a % chance of the event occurring. Now let's say I build another model, and I want to see ...
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58 views

Interpreting LD1 and LD2 in lda in R

I'm conducting an experiment in R. I am using the rattle library that contains a sample of the wine related data. Within this ...
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1answer
47 views

plot LDA fit using R function plot()

I am doing the lab section: classifying the stock data using LDA in the book "Introduction to Statistical Learning with Applications in R", here is the lab video. Basically, this lab uses LDA to ...
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12 views

Classifying after solving discriminant function

I have a set of data (7 variables) that are used as input to ultimately making a decision to approve or not approve something. I've generated two discriminant functions that I'm happy with - one for ...
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0answers
17 views

Bagging Improvement for classification problems

Breiman proved that bagging improves the accuracy of regression. How could this be proven for a classifier model?
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17 views

Fisher kernel or KL divergence?

I am currently reading about pLSA and LDA and how can I apply these methods on calculating document similarity. I got a feeling that common similarity measure used in pLSA is Fisher kernel, but for ...
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28 views

Testing significance of linear discriminants

I have run a discriminant analysis and would like to test the significance of each resulting discriminant function - i.e., does each discriminant function contribute to the separability of the groups? ...
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27 views

How to understand “MANOVA” and multiple discriminant analysis are special cases of canonical correlation?

I am reading a statistical book which writes, Canonical correlation represents one way in which we can examine the relationship between multiple dependent variables ($\bf{Y}$) and multiple ...
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98 views

Caret feature selection [RFE] yields different features depending on reference level of two-class dependent measure

I'm using RFE from the caret package in R to select variables to be used in a linear discriminant analysis. The outcome is a binary factor, but depending on which level of the factor is used as the ...
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28 views

Why can I use the posterior probability of a classifier as a new classifier?

I have read that, when doing discriminant analysis, you can use the posterior probability you obtain using your classifier as a new fine-tuned classifier. Can anyone talk me through the rationale of ...
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32 views

Solution of Fisher LDA

I'm trying to understand the Fishers LDA. In the book I am using there is explained that one has to maximize expression $$\frac{\left( a^T\cdot \bar{x}_2-a^T\cdot \bar{x}_1 \right)^2}{a^T\cdot ...
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115 views

Obtaining significance for variables in a linear discriminant function analysis

I have run a linear discriminant function analysis using the lda() function in the MASS library to determine which of 6 ...
4
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1answer
73 views

Using kernels with Fisher's linear discriminant analysis

I am a bit stuck implementing the Kernel Fisher Discriminant. $$ J(\mathbf{w}) = \frac{\mathbf{w}^{\text{T}}\mathbf{S}_B^{\phi}\mathbf{w}}{\mathbf{w}^{\text{T}}\mathbf{S}_W^{\phi}\mathbf{w}} $$ $$ ...
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13 views

Analogies between Gaussian Discriminant Analysis and Joint Probability Distribution

Can I say GDA is like a full joint probability distribution over all the feature random variables? I mean, if we are given some random variables, we try to inject some conditional independencies, and ...
2
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38 views

Sample lower bound for binary classification in Linear Discriminant Analysis?

Below is a description of this problem: Suppose the label $Y\in\{1,0\}$ in binary classification satisfies $\Pr[Y=1]=\Pr[Y=0]=\frac{1}{2}$, and $p(X|Y=1)=\mathcal{N}(\mu_1,\Sigma)$, ...
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399 views

How to calculate Fisher criterion weights?

I am studying pattern recognition and machine learning, and I ran into the following question. Consider a two-class classification problem with equal prior class probability $$P(D_1)=P(D_2)= ...
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114 views

Plotting QDA projections in R

When doing discriminant analysis using LDA or PCA it is straightforward to plot the projections of the data points by using the two strongest factors. This can be done in R by using the x component ...
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34 views

What is the heuristic to decide number of components for LDA dimensionality reduction?

In the PCA case, I prefer to plot the variance and choose number of components regarding that plot's breaking point. In the LDA (linear disriminant analysis) case, what can be used for such an ...
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16 views

Different coefficients of linear discriminants with the same raw data

I have just tried two ways to perform a linear discriminant analysis. Mode 1 This is the data, divided in two tables (printed from screen using R commander): They belong respectively to the two ...
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158 views

Using results of Canonical Discriminant Analysis to get overall variable importance?

I have a dataset with thousands of observations pre-assigned to 18 groups and with measures for 8 different variables. I am using canonical discriminant analysis to see how separable my 18 groups are. ...
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91 views

Discrimination between measurements made at different points in time

I would like to ascertain what variables discriminate best between experimental conditions in a repeated-measures experimental design. I have performed Repeated Measures MANOVA to determine whether ...
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32 views

How to preprocessing category data for discriminant analysis

I want to do discriminant analysis for five set observation data (five category) using LDA. From references, most of them suggesting to apply some preprocessing first (i.e. transformation, center, ...
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86 views

Multivariate normality in Discriminant Analysis when using dummy variables

I've studied statistics now for almost two years and I'm starting to believe I have missed something very fundamental. I'm doing discriminant analysis where, as I understand it, I can use dummy ...
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1answer
221 views

LDA, PCA and k-means: how are they related?

I am trying to understand how linear discriminant analysis (LDA) is related to principal component analysis (PCA) and k-means clustering method. As an example, here is a comparison between PCA and ...
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31 views

LDA with three variabilities

In a classical linear discriminant analysis (LDA), we usually have only two variabilities to handle (the between classes and the between individual variability). Usually LDA is used to maxmize the ...
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23 views

Individual factor significance in multilevel sPLS-DA

I recently was asked by reviewers to "include p-values" with my multilevel sparse partial least squares analysis. In brief, I have a nested design with two factors, say treatment and sampling region. ...
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295 views

Explanatory variables with linear discriminant analysis

I have a set of data which contains a mix of continuous, categorical variables etc. I wanted to apply linear discriminant analysis however, from some research on the Internet I understand that ...
3
votes
2answers
172 views

Dimensionality reduction technique similar to LDA when class labels are probabilistic

Given discrete class labels, say True and False, LDA (linear discriminant analysis) can be used to perform discriminant dimensionality reduction and attempt to find a subspace that best separates the ...
2
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1answer
824 views

How to follow up a factorial MANOVA with discriminant analysis?

This is a follow-up to to my previous question: How can MANOVA report a significant difference when none of the univariate ANOVAs reaches significance? I have two IVs with each having three levels ...
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1answer
88 views

When to use linear discriminant function and when logistic regression? [duplicate]

I am trying to find out when for creating classification rule to use linear discriminant function and when to use logistic regression? I need to help to find information sources to this topic. Any ...
2
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0answers
39 views

Posterior probabilities as LDA output [closed]

My colleague found @MichaelChernick's post on collinear variables in multiclass lda training. It may be the answer to a very tough question I have had a hard time getting answered. Can someone confirm ...
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55 views

Best time to contact: logistic regression loop or discriminant analysis

I want to do a contactability model which gives for each phone the best combination of time-day to be called. My data is the register of each trial and the result (contacted or not) by day and time. ...