Fisher's Discriminant Analysis: Write a program to perform Fisher's Dis- criminant Analysis for the given data...

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Fisher's Discriminant Analysis: Write a program to perform Fisher's Dis- criminant Analysis for the given data sets. The dataset is given in form of a large matrix X = [X₁X₂... Xc] € RnxCk, where X. E Rnxk is the data for each of the classes c = 1,2,..., C. C = 5 and k 100 in all the examples, but n = changes. 1. Compute mean e of each class, for c=1,2,..., C. 2. Compute within class scatter matrix Sw and between class scatter matrix St 3. Perform generalized eigen-value decomposition using [V,D] = eig (Sb, Sw, 'chol'); 4. Reorder solution using V = fliplr (V) and D = flipud (fliplr (D)). 5. Set U = V(:,1:d) and project Z = UT X. As part of your solution: (1) gener- ate a plot of the eigenvalues, (2) show a colored 2D scatter plot of the projected data. Fisher's Discriminant Analysis: Write a program to perform Fisher's Dis- criminant Analysis for the given data sets. The dataset is given in form of a large matrix X = [X₁X₂... Xc] € RnxCk, where X. E Rnxk is the data for each of the classes c = 1,2,..., C. C = 5 and k 100 in all the examples, but n = changes. 1. Compute mean e of each class, for c=1,2,..., C. 2. Compute within class scatter matrix Sw and between class scatter matrix St 3. Perform generalized eigen-value decomposition using [V,D] = eig (Sb, Sw, 'chol'); 4. Reorder solution using V = fliplr (V) and D = flipud (fliplr (D)). 5. Set U = V(:,1:d) and project Z = UT X. As part of your solution: (1) gener- ate a plot of the eigenvalues, (2) show a colored 2D scatter plot of the projected data.

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Certainly Below is a MATLAB code snippet that performs Fishers Discriminant Analysis based on the st... View the full answer