boost_error(useless).cpp

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 #include "peddetect.h"

int main (int argc, char **argv)
{

/* STEP 2. Opening the file */
//1. Declare a structure to keep the data
  CvMLData cvml;
//2. Read the file
  cvml.read_csv ("/home/pedrobatista/workingcopy/lar3/perception/pedestrians/PedestrianDetect/train_seed1234_rand.csv");
//3. Indicate which column is the response
  cvml.set_response_idx (0);
    
/* STEP 3. Splitting the samples */
//1. Select 40 for the training
  CvTrainTestSplit cvtts (8000, true);
//2. Assign the division to the data
  cvml.set_train_test_split (&cvtts);

  printf ("Training ... ");
/* STEP 4. The training */
//1. Declare the classifier
  CvBoost boost;
//2. Train it with 100 features
  boost.train (&cvml, CvBoostParams (CvBoost::REAL,1500, 0.95, 2, false, 0),
               false);
                
/* STEP 5. Calculating the testing and training error */
// 1. Declare a couple of vectors to save the predictions of each sample
  std::vector<float> train_responses, test_responses;
// 2. Calculate the training error
  float fl1 = boost.calc_error (&cvml, CV_TRAIN_ERROR, &train_responses);
// 3. Calculate the test error
  float fl2 = boost.calc_error (&cvml, CV_TEST_ERROR, &test_responses);
  
  cout<<"Error train: "<<fl1<<endl;
  
  cout<<"Error test: "<<fl2<<endl;

/* STEP 6. Save your classifier */
// Save the trained classifier
//   boost.save ("./trained_boost_8000samples-1000ftrs.xml", "boost");

  return 0;
}