# Questions tagged [lda-classifier]

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### Adding $1$ feature to data point to avoid bias

Given data point $x\in X,\ x\in \mathbb{R}^p$, once we resolve the parameters of the linear discriminant model, we will have $\hat{B} = (X^TX)^{-1}X^TY$, where $Y \in \mathbb{R}^{N\times K}$ is the ...
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### Comparison of classifier confusion matrices

I tried implementing Logistic regression, Linear Discriminant Analysis and KNN for the smarket dataset provided in "An Introduction to Statistical Learning" in python. Logistic Regression ...
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### 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. ...
189 views

### Problems with Linear Discriminant Analysis Classifier

I wrote two functions for determining the linear discriminant classifier of an EEG data set. The data set consists of preprocessed EEG data 𝑋∈𝑅5×62×5322 and stimulus labels 𝑌∈𝑅2×5322 during a copy-...
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### Linear Discriminant Analysis + bayesian theorem = LDA classifier??

I am new to machine learning and as I learn about Linear Discriminant Analysis, I can't see how it is used as a classifier. I can understand the difference between LDA and PCA and I can see how LDA ...
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### Linear Discriminant Analysis, which parameters can be tunned in cross validation set up?

I am implementing Linear Discriminant Analysis in R, which parameters can be tunned in cross validation set up? In regularized mode called penalizedLDA there are parameters which are optimised but I ...
135 views

### Linear Discriminant Analysis (LDA) , Removing colinear features in cross validation set up is correct or not?

My data is a matrix with 725 features and 667 observations which have binary data(either 0 or 1). my target variable is a univariate which has two classes (either 0 or 1). I removed the features which ...