title: Using Custom Dataset With nprtool
body: <p>Am trying to clasify objects using neural networks' <code>nprtool</code> in MATLAB. However, loading the data (input and outputs) is my problem. I have gone through the given examples in the documentation but am not able to customize the inputs and outputs. Part of the dataset is given below for your reference; assume that the data is already normalized. How can one use the the MATLAB Neural Network Toolbox <code>nprtool</code> with custom data like these?</p>
  
  <pre><code>% Small vehicles
  XS1 = 1.0e+03 *[3.2730    0.0712    0.0614        5.1480]; % frame 167
  XS2 = 1.0e+03 *[4.4680    0.0869    0.0668        6.2370];% frame 555
  XS3 = 1.0e+03 *[2.5450    0.0742    0.0659        4.6900]; % frame 780
  XS4 = 1.0e+03 *[1.9830    0.0617    0.0477        2.9680]; % frame 826
  XS5 = 1.0e+03 *[2.9090    0.0630    0.0610        4.1600]; % frame 880
  XS6 = 1.0e+03 *[3.8460    0.0797    0.0640        5.6700]; % frame 1283
  
  % Medium vehicles
  XM1 = 1.0e+03 *[4.7770    0.0981    0.0663        6.9560]; % frame 167
  XM2 = 1.0e+03 *[5.1050    0.0997    0.0678        7.4460]; % frame 430
  XM3 = 1.0e+03 *[4.0240    0.0846    0.0619        5.4780]; % frame 2020
  XM4 = 1.0e+03 *[6.9750    0.1165    0.0794        9.6280]; % frame 2982
  XM5 = 1.0e+03 *[5.2040    0.1063    0.0652        7.0810]; % frame 3081
  XM6 = 1.0e+03 *[3.2830    0.0733    0.0645        4.6080]; % frame 4314
  
  % Large vehicles
  XL1 = 1.0e+04 *[1.0092    0.0148    0.0089        1.4948]; % frame 1340
  XL2 = 1.0e+04 *[0.9351    0.0129    0.0096        1.2444]; % frame 1375
  XL3 = 1.0e+04 *[0.6021    0.0141    0.0095        1.5096]; % frame 1625
  XL4 = 1.0e+04 *[0.8734    0.0143    0.0086        1.1868]; % frame 1679
  XL5 = 1.0e+04 *[1.0773    0.0141    0.0100        1.4933]; % frame 2204
  XL6 = 1.0e+04 *[0.8491    0.0118    0.0097        1.0556]; % frame 3535
  
  % CONCATANATING THE OBJECT FEATURES
  XS = [XS1;XS2;XS3;XS4;XS5;XS6];
  XM = [XM1;XM2;XM3;XM4;XM5;XM6];
  XL = [XL1;XL2;XL3;XL4;XL5;XL6];
  
  %  inputs matrix
  X = [XS;XM;XL];
  
  %% OUTPUTS
  YS ={'smallvehicle';'smallvehicle';'smallvehicle';'smallvehicle';'smallvehicle';'smallvehicle'};
  YM ={'mediumvehicle';'mediumvehicle';'mediumvehicle';'mediumvehicle';'mediumvehicle';'mediumvehicle'};
  YL ={'largevehicle';'largevehicle';'largevehicle';'largevehicle';'largevehicle';'largevehicle'};
  
  % outputs matrix
  Y = [YS;YM;YL];
  </code></pre>