1. Download and install MATLAB. Develop the following function using MATLAB
a. Write a script that loads data from a file and display the first five instances. Create a matrix from the loaded instances.
b. Divide the loaded instances into two sets with one set containing 70% of the instances and the other containing 30% of the instances. Save each set into a variable. Name the variables ‘TrainingSet’ and TestingSet’.
c. Save the two new variable to a ‘.mat’ file.
2. Implementing Fisher LDA method using MATLAB.
a. Write functions that take the provided data set and compute the optimal projection vector following the fisher criterion.
b. The output from the main function must be the identified projection vector.
3. Write functions to evaluate the LDA method using MATLAB.
a. Write a script to perform cross-validation and report the average accuracy, standard deviation, sensitivity, and specificity.
NOTE: There is no requirement to develop a GUI to visualize the intermediate or the results.
A report that includes the following items is due in addition to the source code for the functions:
- A description of each function,
- How to run the functions to get the reported results, and
- The experimental results.
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I am RANDHIR KUMAR faculty of Mathematics for 11th. 12th. I.I.T foundation and also for degree levels having 27 years experience
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Hello,
I am a research scholar working in Machine Learning and Computer Vision. I have read the problem and understood it quite well, and I think I have the relevant knowledge and expertise to solve it. I have worked on Matlab previously and have the relevant skills to solve this problem. I have also written and published some good research articles and hence I can prepare the report well. I would like to discuss it further and work on the problem.
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I m phd scholler in electronics.
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Thanks