예제 #1
0
def run_all():

  from options import MultiOptions
  opt = MultiOptions()
  #opt.count_number_of_events()

  ### UNSUPERVISED METHOD ### 
  if opt.opdict['method'] == 'kmeans':
    from unsupervised import classifier
    classifier(opt)

  ### SUPERVISED METHODS ###
  elif opt.opdict['method'] in ['lr','svm','svm_nl','lrsk']:
    from do_classification import classifier
    classifier(opt)

    from results import AnalyseResults
    res = AnalyseResults()
    if res.opdict['plot_confusion']:
      res.plot_confusion()

  elif opt.opdict['method'] in ['ova','1b1']:
    from do_classification import classifier
    classifier(opt)

    from results import AnalyseResultsExtraction
    res = AnalyseResultsExtraction()
예제 #2
0
def run_all():

  from options import MultiOptions
  opt = MultiOptions()
  #opt.count_number_of_events()
 
  from do_classification import classifier
  classifier(opt)

  if opt.opdict['method'] == 'lr' or opt.opdict['method'] == 'svm' or opt.opdict['method'] == 'lrsk':
    from results import AnalyseResults
    res = AnalyseResults()
    if res.opdict['plot_confusion']:
      res.plot_confusion()

  else:
    from results import AnalyseResultsExtraction
    res = AnalyseResultsExtraction()
예제 #3
0
def run_all():

    from options import MultiOptions
    opt = MultiOptions()
    #opt.count_number_of_events()

    from do_classification import classifier
    classifier(opt)

    if opt.opdict['method'] == 'lr' or opt.opdict[
            'method'] == 'svm' or opt.opdict['method'] == 'lrsk':
        from results import AnalyseResults
        res = AnalyseResults()
        if res.opdict['plot_confusion']:
            res.plot_confusion()

    else:
        from results import AnalyseResultsExtraction
        res = AnalyseResultsExtraction()