I have created dataset of 94 B-scan images (76 training + 18 testing) consists of 3 classes (metal pipe, steel box, plastic box). I have extracted statistical features from images the size of training features is 76*6. and I have assigned labels using traindb.Labels, I can able to load input data as training features from work space but Iam unable to load target data.
My goal is to classify the three objects using NN classifier. I have classified these objects using ECOC-SVM but I'm unable to load target data using nntool. I'm attaching my code and database for your reference. please help me.
Dear Santhosh kumar Buddepu
Take a look: https://stackoverflow.com/questions/44426019/issue-with-nnstart-in-matlab-tool
Kind Regards
Qamar Ul Islam
Thank you Qamar Ul Islam for reply
but my training labels is 76*1 categorical (metal pipe,steel box, plastic box) its not a numbers. it is showing the error like " Targets T is not a matrix or cell array."
my target data should be 76*3 defining which of three classes each input is assigned to. Classes are represented by a 1 in row 1, 2 or 3.
1. metal pipe #1
2. steel box #2 3. plastic box #3
how to assign numbers to my target data
my labels are 76*1 categorical (metal pipe-19, plastic box-28, steel box-29). I need to classify into 3 classes and my target data should be 76*3 which is in the form of
1 1 1....1(19) 0 0 0... (remaining)
0 0 0..0(19) 1 1 1...1(28) 0 0...0(remaining)
0 0 0......0(47) 1 1 1...1(29)
how to make target data like this?
First, make the input and target, i.e., 'i', and target 't' in matrix form in the Matlab. Run that matrix and save it in a workspace as i and t.
Then, start nntool or nnstart. You select the input as i and target as t, making a network. By choosing the network, you can select the inputs and target and various parameters such as no of the hidden layer, no of neurons in each hidden layer, no of epochs, etc., and then train your network accordingly. or
you can go through a link for better understanding.
https://www.youtube.com/watch?v=q-iWO9CLC08
Regards
Prince
Dear Santhosh kumar Buddepu
As Prince Kumar rightly suggested you may first save your inputs and targets separately.
And then process them with optimization in the number of hidden neurons and number of epochs.
For further study, please refer
https://in.mathworks.com/matlabcentral/answers/167288-importing-target_dataset-from-an-excel-file-to-a-neural-network-toolbox-for-pattern-recognition-npr
Hope I am not too late.
Regards,
Geetali
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