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Part I Single Feature 1 . Create a matlab script that will perform each of the steps required for this exercise. 2 . Load partOneData
Part I Single Feature
Create a matlab script that will perform each of the steps required for this exercise.
Load partOneDatamat into the matlab environment included in blackboard as part of the
assignment
Create a histogram for each of the class distributions classOne classTwo Plot each of the
histograms on the same figure use bins The figure should contain a title, legend and the x
and y axis should be labeled appropriately.
Report the prior probability of classOne? Hint: Number of classOne samples divided by all
samples
Report the prior probability of classTwo? Hint: see above hint, but for classTwo
Create a random partition of the data, splitting each of the classes into training and
testing.
a Using only the training data, find the maximum likelihood estimator for the following
parameters:
i Class One: sigma Part I Single Feature
Create a matlab script that will perform each of the steps required for this exercise.
Load 'partOneData.mat' into the matlab environment included in blackboard as part of the
assignment
Create a histogram for each of the class distributions classOne classTwo Plot each of the
histograms on the same figure use bins The figure should contain a title, legend and the
and y axis should be labeled appropriately.
Report the prior probability of classOne? Hint: Number of classOne samples divided by all
samples
Report the prior probability of classTwo? Hint: see above hint, but for classTwo
Create a random partition of the data, splitting each of the classes into training and
testing.
a Using only the training data, find the maximum likelihood estimator for the following
parameters:
i Class One:
ii Class Two:
b Classify each of the samples in the test partition using a Bayesian classifier you must
create a function that will do this Report the prediction accuracy for class one and class
two.
Hint: You will need to create a method that, given the mean and standard deviation of a
distribution, determines the probability that belongs to the distribution.
Matlab template below:
function probability computeGaussianDensitymean stdDev,
Your code to calculate the Gaussian density here
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