def __init__(self,pinakasA,mywidth,classifier_code):
self.code=classifier_code
if self.code=="svm":
classifier=SVMAnomalyClassifier(pinakasA,mywidth)
elif self.code=="gmm":
classifier=GMMAnomalyClassifier(pinakasA,mywidth)
else:
raiseException("Unrecognized Name")
#if isinstance(classifier,SVMAnomalyClassifier):
#print "einai SVMAnomalyClassifier"
#if isinstance(classifier,AnomalyClassifier):
#print "einai AnomalyClassifier"
self.width=mywidth
classifier.trainWithDataset(pinakasA,self.width)
trained_pickled = open('/home/mike/svn/nasia/trunk/philosophers/src/anomaly_detection/scripts/results/trained.pkl', 'wb') #apo8ikevei to trained montelo sto data.pkl
pickle.dump(classifier, trained_pickled, -1)
sys.exit()
def __init__(self,pinakasA,mywidth,classifier_code):
self.code=classifier_code
if self.code=="svm":
classifier=SVMAnomalyClassifier(pinakasA,mywidth)
elif self.code=="gmm":
classifier=GMMAnomalyClassifier(pinakasA,mywidth)
else:
raiseException("Unrecognized Name")
if isinstance(classifier,SVMAnomalyClassifier):
print "einai SVMAnomalyClassifier"
if isinstance(classifier,AnomalyClassifier):
print "einai AnomalyClassifier"
self.width=mywidth
classifier.trainWithDataset(pinakasA,self.width)
trained_pickled = open('trained.pkl', 'wb') #apo8ikevei to trained montelo sto data.pkl
pickle.dump(classifier, trained_pickled, -1)
sys.exit()