def __init__(self, iteration):
QueryStrategy.__init__(self, iteration)
multiclass_model = self.iteration.update_model.models['multiclass']
multiclass_exp = self.iteration.update_model.models_exp['multiclass']
self.all_instances = RareCategoryDetectionAnnotationQueriesExp(self.iteration, 'all', 0, 1,
multiclass_model = multiclass_model,
multiclass_exp = multiclass_exp)
def __init__(self, iteration):
QueryStrategy.__init__(self, iteration)
num_annotations = self.iteration.experiment.conf.batch
proba_min = None
proba_max = None
self.annotations = UncertainAnnotationQueries(self.iteration,
num_annotations,
proba_min, proba_max)
def __init__(self, iteration):
QueryStrategy.__init__(self, iteration)
eps = self.iteration.conf.eps
self.uncertain = UncertainAnnotationQueries(
self.iteration, self.iteration.conf.num_uncertain, 0, 1)
self.malicious = RareCategoryDetectionAnnotationQueriesExp(
self.iteration, 'malicious', 1 - eps, 1)
self.benign = RareCategoryDetectionAnnotationQueriesExp(
self.iteration, 'benign', 0, eps)
def executionTimeDisplay(self):
binary_model = PlotDataset(None, 'Binary model')
malicious = PlotDataset(None, 'Malicious Analysis')
malicious.setLinestyle('dotted')
malicious.setColor(colors_tools.getLabelColor('malicious'))
benign = PlotDataset(None, 'Benign Analysis')
benign.setLinestyle('dashed')
benign.setColor(colors_tools.getLabelColor('benign'))
return [binary_model, malicious, benign
] + QueryStrategy.executionTimeDisplay(self)
def executionTimeDisplay(self):
clustering = PlotDataset(None, 'Analysis')
return [clustering] + QueryStrategy.executionTimeDisplay(self)
def executionTimeMonitoring(self):
line = [self.all_instances.analysis_time]
line += QueryStrategy.executionTimeMonitoring(self)
return line
def executionTimeHeader(self):
header = ['clustering']
header += QueryStrategy.executionTimeHeader(self)
return header
def __init__(self, iteration):
QueryStrategy.__init__(self, iteration)
multiclass_model = self.iteration.train_test_validation.models[
'multiclass']
self.all_instances = RareCategoryDetectionAnnotationQueries(
self.iteration, 'all', 0, 1, multiclass_model=multiclass_model)
def executionTimeMonitoring(self):
line = [self.iteration.train_test_validation.times['binary']]
line += QueryStrategy.executionTimeMonitoring(self)
return line
def executionTimeHeader(self):
header = ['logistic_regression', 'naive_bayes']
header += QueryStrategy.executionTimeHeader(self)
return header
def __init__(self, iteration):
QueryStrategy.__init__(self, iteration)
self.unsure = AladinAnnotationQueries(self.iteration, self.conf)
def executionTimeHeader(self):
header = ['binary_model', 'malicious_clustering', 'benign_clustering']
header += QueryStrategy.executionTimeHeader(self)
return header
def executionTimeMonitoring(self):
line = [self.iteration.train_test_validation.times['binary']]
line += [self.malicious.analysis_time, self.benign.analysis_time]
line += QueryStrategy.executionTimeMonitoring(self)
return line
def __init__(self, iteration):
QueryStrategy.__init__(self, iteration)
num_annotations = self.iteration.experiment.conf.batch
self.random_annotations = RandomAnnotationQueries(self.iteration, num_annotations)
def __init__(self, iteration):
QueryStrategy.__init__(self, iteration)
b = self.iteration.conf.b
num_annotations = self.iteration.conf.batch
self.annotations = CesaBianchiAnnotationQueries(self.iteration, b, num_annotations)
def executionTimeMonitoring(self):
line = [self.iteration.update_model.times['binary']]
line += QueryStrategy.executionTimeMonitoring(self)
return line
def executionTimeMonitoring(self):
line = [self.unsure.lr_time, self.unsure.nb_time]
line += QueryStrategy.executionTimeMonitoring(self)
return line
def executionTimeHeader(self):
header = ['binary_model']
header += QueryStrategy.executionTimeHeader(self)
return header
def executionTimeDisplay(self):
lr = PlotDataset(None, 'Logistic Regression')
lr.setLinestyle('dotted')
nb = PlotDataset(None, 'Naive Bayes')
nb.setLinestyle('dashed')
return [lr, nb] + QueryStrategy.executionTimeDisplay(self)
def executionTimeDisplay(self):
binary_model = PlotDataset(None, 'Binary model')
return [binary_model] + QueryStrategy.executionTimeDisplay(self)
def __init__(self, iteration):
QueryStrategy.__init__(self, iteration)
num_annotations = self.iteration.conf.batch
self.annotations = GornitzAnnotationQueries(self.iteration,
num_annotations)