implement the ANN-based classifier for three class of vehicles-train, bus and two wheeler

 The first three columns correspond to the output label-the type of vehicle chosen by a person for office travel. remaining columns are the input characteristics based on the vehicle mode that is chosen. Use only selected input characteristics for classifier. Here is procedure to follow:

1. select 150 rows (4-10)columns from the text and read,normalize and input the data for training

2. selct 150 rows and (1-3) colums and read as data for train output(train data labels)

3.select (151-182)rows and (4-10)colums from the text and read,normalize and input data for test

4. convert the obtained output from neural network in to a form similar to train data labels to produce output labels

5. Compute the accuracy of classifier in %

Answer 1

[Greg Heath]

%1. select 150 rows (4-10)columns from the text and read,normalize and input the data for training.

Then transpose to obtain

 [ I Ntrn ] = size(xtrn)   % % I = 7, Ntrn = 150

%2. selct 150 rows and (1-3) colums and read as data for train output(train data labels)

Convert the target code to rows of the eye(3). Then transpose to obtain

 [ O Ntrn ] = size(ttrn)   % % O = 3, Ntrn = 150

% Train a classifier

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%3.select (151-182)rows and (4-10)colums from the text and read,normalize and input data for test

 [ I Ntst ] = size(xtst)   % I = 7, Ntst = 32

ytst = vec2ind(net(xtst));

4. convert the obtained output from neural network in to a form similar to train data labels to produce output labels

5. Compute the accuracy of classifier in %

Hope this helps.

Thank you for formally accepting my answer

Greg

Answer 2

[Image Analyst]

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