I have a data set that I would like to categorize into 3 groups. For practice I made a matrix of 100rows by 4 columns to simulate 100 data points with 4 pieces of information each (in my actual data these are easting, northing, strike, and dip).
My problem is that after running the neural network clustering app (nctool), I have no idea what to do with the code that was generated. Ive saved it both as a MATLAB function and as a MATLAB Matrix only function.
But when I open the .m files and try to run them I get errors immediately.
Specifically, my (100,4) matrix is called Input, and thats all I ran through the model. That file is open, and both it and the neural network generated file are in the same folder.
When I open and run the .m file, all I get is
Error using TestCodeOption2 (line 25)
Not enough input arguments.
Error in run (line 96)
evalin('caller', [script ';']);
Line 25 is the very first line without the % comment designator.
I suppose that this file has a variety of new variables and or matrices that I need to generate.
but I'm completely lost.
I appreciate any help.
Thanks!

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Greg Heath
Greg Heath 2015 年 4 月 24 日

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There are very simple examples in the command line help and doc documentation
help fitnet % curvefitting and regression
doc fitnet
help patternnet % pattern-recognition and classification
doc patternnet
I have posted many examples in the NEWSGROUP and ANSWERS. For classification, include the search words
greg patternnet
Hope this helps.
Greg
PS Transpose your input and target matrices

1 件のコメント

Josh White
Josh White 2015 年 4 月 24 日
I'll go take a look now, thank you.
Also, after going through the examples several more times I realized that i needed to just use this command:
a = net(houseInputs);
only customized to my data:
a = NNtest1(Input)
and it gave me the results.
I'm also extremely proud to say that I've managed to do the same using the classification tool!
I know how powerful MATLAB is, and appreciate all the help you guys give, especially to beginners like me asking the questions that would have been answered in a basic MATLAB course in school, if I'd been less boneheaded and taken one.
Thanks!

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