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Linear Discriminant Analysis (LDA)
- The first step in LDA is to calculate the mean of each feature within each class.
- In this step, we calculate the scatter matrix which measures the spread of the data within and between the classes.
- Next, we compute the eigenvectors and eigenvalues from the scatter matrices to find the optimal projection.
- Finally, we transform the data into a lower-dimensional space and visualize it in a scatter plot.
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