ps4 (1)

ps4 (1) - Problem Set 4 MAS 622J/1.126J Pattern Recognition...

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Unformatted text preview: Problem Set 4 MAS 622J/1.126J: Pattern Recognition and Analysis Due Wednesday, 25 October 2006 [Note: As usual, please use Python or Matlab when asked to plot data or write a program.] Problem 1: ML Estimation After Dimensional- ity Reduction Download this problem set’s data set files from the course webpage. All these data sets consist of 3-dimensional data. There are data sets for two classes, class and class 1. For each class, there are two training data sets, ‘A’ and ‘B,’ and one testing data set. a. Use Matlab or Python to reduce the dimensionality of the ‘A’ training data set for both classes from 3-dimensional to 1-dimensional using Prin- cipal Component Analysis (PCA). As usual, include your program in your answer. b. Use Matlab or Python to reduce the dimensionality of the ‘A’ training data set for both classes from 3-dimensional to 1-dimensional using Fisher Linear Discriminant (FLD). As usual, include your program in your an- swer. c. Use Matlab or Python to compute the maximum-likelihood mean and variance of the dimension-reduced ‘A’ training data set for both classes....
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ps4 (1) - Problem Set 4 MAS 622J/1.126J Pattern Recognition...

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