“matlab”
Two different sets of training and testing data (A and B)
The training data has classifications in the last column. There are no classifications for the testing data.
Data A has classes 1,2 and 3.
Data B has classes 2 and 4.
Use the training data to train the neural network; have your trained network evaluate the test data.
For both A and B explain how to construct your network architectures and how you trained them.
Plot the MSE as a function of training Epoch.
Make a table showing the classification accuracy after training. For example, for data A, let each row of the table (1,2,3) indicate when a particular class is presented to the network, let each column (1,2,3) tally the number of classifications made for each class.
Create tables using the testing data. Each row will specify a test instance. For data set A, the first 4 columns will specify the elements of the test instance, the fifth column will specify the class for that instance made by your network. For data set B, the first 9 columns will specify the elements of the test instance, the tenth column will specify the class for that instance made by your network.
for each data set use the following methods.
Rosenblatt’s Perceptron
“I will send the data set files once I know you can do it”
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