# 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 ...

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### Treatment of outliers produced by Kurtosis

I was wondering if anyone could help me with information about Kurtosis (i.e. is there any way to transform your data to reduce it?) I have a questionnaire dataset with a large number of cases and ...
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 ...
462 views

### Why prediction of a predicted variable from a discriminant analysis is imperfect

I am puzzled by something I found using Linear Discriminant Analysis. Here is the problem - I first ran the Discriminant analysis using 20 or so independent variables to predict 5 segments. Among the ...
918 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? ...
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### 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 ...
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### Deriving total (within class + between class) scatter matrix

I was fiddling with PCA and LDA methods and I am stuck at a point, I have a feeling that it is so simple that I can't see it. Within-class ($S_W$) and between-class ($S_B$) scatter matrices are ...
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### Variant of discriminant analysis for known multiple independent classifications?

I have a large data set: over 100,000 data points, each with 60 dimensions. I want to display the data in 2D to visibly maximize the separation between classes, which I know for each point. I asked a ...
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 ...
148 views

### LDA vs. perceptron

I am trying to get a feel for how LDA 'fits' within other supervised learning techniques. I have already read some of the LDA-esque posts on here about LDA. I am already familiar with the perceptron, ...
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 ...
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 ...
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### 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 ...
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### How do you identify the variables that separate several groups?

I don't have much background on statistics. I am working on multivariate morphometrics of a sample of frogs. I have a data matrix of 19 variables (continuous characteristics) for around 250 samples. ...
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### Choosing variables for Discriminant Analysis

I've 110 variables & 200 data points. Of this 110 variables, one is group variable (say "brown eye","blue eye"). I want to use discriminant analysis to classify the groups based on remaining 119 ...
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### 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 ...
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### Alternatives to stepwise discriminant analysis for feature selection on hyperspectral data

I am new to R and to hyperspectral data analysis. However, in my research, I have found that many warn against using Stepwise discriminant analysis (using Wilk's Lambda or Mahalanobis distance) for ...
154 views

### Using QDA for Non-Gaussian distributions

I am evaluating a Quadratic Discriminant Analysis (QDA) classifier on a high-dimensionality feature set. The features come from highly non-Gaussian distributions. However, when I transform the ...
938 views

### Why are Gaussian “discriminant” analysis models called so?

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 ...
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### 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 ...
926 views

### How to interpret a predictor with a positive structure coefficient and a negative standardised coefficient in discriminant function analysis?

I am doing a discriminant function analysis and I have four continous independent variables and one categorical dependent variable (that has 3 groups). I have chosen to do this analysis to see how ...
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 ...
354 views

### Theory on discriminant analysis in small sample size conditions

I see a similarity between a problem I'm working on and Linear (or Quadratic) Discriminant Analysis when the sample size is smaller than $p+1$. I'm interested in theory bounding the generalization ...
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### Linear Discriminant Analysis: Using subject as classification

I have a problem where I need to identify from which subject a particular set of data points came. More specifically, my problem is that I need to demonstrate that my subjects (N=9) can be ...
105 views

### Prediction using SVD and Fisher's linear discriminant

Where can I get an explanation of the procedure used when making a prediction using SVD? Let me elaborate a bit more. Suppose you have data in a matrix $A$ containing two classes. In particular, you ...
144 views

### LDA, Significance of orthonormality- Trace Ratio Maximization

The objective of fisher linear discriminant analysis can be formulated as maximizing $\frac{Tr[X^TAX]}{Tr[X^TBX]}$ over $X$ where $A$ and $B$ are positive semi-definite with orthonormality constraints ...
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### How do I test whether I can properly apply LDA?

I have some data which works nicely with JMP's canned linear discriminant analysis (LDA), but after reading about LDA I'm not sure if the analysis is valid. The Wiki article notes a fundamental ...
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### Optimization parameter for classification [closed]

I do not have enough knowledge about optimization. My problem is simple. Lets say I have 100 classes. Each class contains some instances (images). The feature vector obtained from a particular image ...
96 views

### Why is there a sharp elbow in my ROC curves?

I have some EEG data sets that I am testing against two classes. I can get a decent error rate from LDA (the class-conditional distributions aren't Gaussian, but have similar tails and good enough ...
236 views

### How does Fisher LDA work?

Intuitively, how does Fisher LDA work? From this Linear discriminant analysis and Bayes rule I completely understood the Bayesian approach but I'm not able to relate it to the Fisher's one described ...
247 views

### LDA projection for classification

I am dealing with 2 class LDA classification problem. During a test phase (after training), I'm trying to project a feature vector to lower dimensional space. How do we get the projected test ...
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### Role of orthogonal constraints (X^TX=I) in linear discriminant analysis?

What is the role of the orthogonal constraints in Linear Discriminant Analysis? Why would it work/not work if the fraction of the traces is maximized without that constraint? Wouldn't its still ...
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### Quadratic discriminant analysis (QDA) with qualitative predictors in R

I need your help with a Statistical Learning homework in R. I have to perform classification over this dataset: mammographic masses predicting Severity (0="not severe",1 = "severe) using these ...