def fromJson(obj, session):
experiment = DescriptiveStatisticsExperiment(obj['project'],
obj['dataset'],
session,
create=False)
Experiment.expParamFromJson(experiment, obj, None)
return experiment
def fromJson(obj, secuml_conf):
conf = ClassifierConfFactory.getFactory().fromJson(
obj['classification_conf'])
experiment = ClassificationExperiment(secuml_conf)
experiment.initExperiment(obj['project'], obj['dataset'], create=False)
Experiment.expParamFromJson(experiment, obj, conf)
return experiment
def fromJson(obj, session):
experiment = ValidationExperiment(obj['project'],
obj['dataset'],
session,
create=False)
Experiment.expParamFromJson(experiment, obj, Configuration())
return experiment
def setConf(self, conf, features_file, annotations_filename=None,
annotations_id=None):
self.query_strategy = conf.query_strategy
Experiment.setConf(self, conf, features_file,
annotations_filename=annotations_filename,
annotations_id=annotations_id)
if self.conf.validation_conf is not None:
self.test_exp = self.createValidationExperiment()
def export(self):
Experiment.export(self)
if self.conf.test_conf.method == 'dataset':
self.test_exp.export()
filename = path.join(self.getOutputDirectory(),
'test_experiment.txt')
with open(filename, 'w') as f:
f.write(str(self.test_exp.experiment_id) + '\n')
def fromJson(obj, session):
conf = ClusteringConfFactory.getFactory().fromJson(obj['conf'])
experiment = ClusteringExperiment(obj['project'],
obj['dataset'],
session,
create=False)
Experiment.expParamFromJson(experiment, obj, conf)
return experiment
def fromJson(obj, secuml_conf):
experiment = ActiveLearningExperiment(secuml_conf)
experiment.initExperiment(obj['project'], obj['dataset'],
create=False)
conf = ActiveLearningConfFactory.getFactory().fromJson(obj['conf'])
Experiment.expParamFromJson(experiment, obj, conf)
experiment.query_strategy = obj['query_strategy']
return experiment
def export(self):
Experiment.export(self)
if self.conf.validation_conf is not None:
self.test_exp.export()
filename = path.join(self.getOutputDirectory(),
'test_experiment.txt')
with open(filename, 'w') as f:
f.write(str(self.test_exp.experiment_id) + '\n')
def __init__(self,
project,
dataset,
session,
experiment_name=None,
parent=None,
logger=None,
create=True):
Experiment.__init__(self, project, dataset, session, experiment_name,
parent, logger, create)
self.already_trained = None
def generateParser():
parser = argparse.ArgumentParser(
description='Clustering of the data for data exploration.')
Experiment.projectDatasetFeturesParser(parser)
algos = ['Kmeans', 'GaussianMixture']
subparsers = parser.add_subparsers(dest='algo')
factory = ClusteringConfFactory.getFactory()
for algo in algos:
algo_parser = subparsers.add_parser(algo)
factory.generateParser(algo, algo_parser)
return parser
def generateParser():
parser = argparse.ArgumentParser(
description='Clustering of the data for data exploration.')
Experiment.projectDatasetFeturesParser(parser)
subparsers = parser.add_subparsers(dest='algo')
subparsers.required = True
factory = ClusteringConfFactory.getFactory()
algos = factory.getAlgorithms()
for algo in algos:
algo_parser = subparsers.add_parser(algo)
factory.generateParser(algo, algo_parser)
return parser
def setConf(self,
conf,
features_file,
annotations_filename=None,
annotations_id=None):
Experiment.setConf(self,
conf,
features_file,
annotations_filename=annotations_filename,
annotations_id=annotations_id)
if self.conf.test_conf.method == 'dataset':
self.test_exp = self.createTestExperiment()
def generateParser():
parser = argparse.ArgumentParser(
description='Active Learning',
formatter_class=argparse.RawTextHelpFormatter)
Experiment.projectDatasetFeturesParser(parser)
subparsers = parser.add_subparsers(dest='strategy')
subparsers.required = True
factory = ActiveLearningConfFactory.getFactory()
strategies = factory.getStrategies()
for strategy in strategies:
strategy_parser = subparsers.add_parser(strategy)
factory.generateParser(strategy, strategy_parser)
return parser
def generateParser():
parser = argparse.ArgumentParser(
description='Active Learning',
formatter_class=argparse.RawTextHelpFormatter)
Experiment.projectDatasetFeturesParser(parser)
strategies = [
'Ilab', 'RandomSampling', 'UncertaintySampling', 'CesaBianchi',
'Aladin', 'Gornitz'
]
subparsers = parser.add_subparsers(dest='strategy')
factory = ActiveLearningConfFactory.getFactory()
for strategy in strategies:
strategy_parser = subparsers.add_parser(strategy)
factory.generateParser(strategy, strategy_parser)
return parser
def __init__(self,
project,
dataset,
session,
experiment_name=None,
logger=None,
create=True):
Experiment.__init__(self,
project,
dataset,
session,
experiment_name=experiment_name,
logger=logger,
create=create)
# query_strategy: vraiment utile ?
self.query_strategy = None
def generateParser():
parser = argparse.ArgumentParser(
description='Learn a detection model. ' +
'The ground-truth must be stored in annotations/ground_truth.csv.')
Experiment.projectDatasetFeturesParser(parser)
models = [
'LogisticRegression', 'Svc', 'GaussianNaiveBayes', 'DecisionTree',
'RandomForest', 'GradientBoosting'
]
subparsers = parser.add_subparsers(dest='model')
factory = ClassifierConfFactory.getFactory()
for model in models:
model_parser = subparsers.add_parser(model)
factory.generateParser(model, model_parser)
## Add subparser for already trained model
already_trained = subparsers.add_parser('AlreadyTrained')
factory.generateParser('AlreadyTrained', already_trained)
return parser
def toJson(self):
conf = Experiment.toJson(self)
conf['__type__'] = 'ActiveLearningExperiment'
conf['query_strategy'] = self.query_strategy
conf['conf'] = self.conf.toJson()
return conf
def toJson(self):
conf = Experiment.toJson(self)
conf['__type__'] = 'ClusteringExperiment'
conf['conf'] = self.conf.toJson()
return conf
def __init__(self, secuml_conf, session=None):
Experiment.__init__(self, secuml_conf, session=session)
self.already_trained = None
def toJson(self):
conf = Experiment.toJson(self)
conf['__type__'] = 'ClassificationExperiment'
conf['classification_conf'] = self.conf.toJson()
return conf
def toJson(self):
conf = Experiment.toJson(self)
conf['__type__'] = 'DescriptiveStatisticsExperiment'
return conf
def generateParser():
parser = argparse.ArgumentParser(
description='Descriptive Statistics of the Dataset')
Experiment.projectDatasetFeturesParser(parser)
return parser
def __init__(self, secuml_conf, session=None):
Experiment.__init__(self, secuml_conf, session=session)
self.query_strategy = None
def toJson(self):
conf = Experiment.toJson(self)
conf['__type__'] = 'ValidationExperiment'
return conf
def fromJson(obj, secuml_conf):
experiment = ValidationExperiment(secuml_conf)
experiment.initExperiment(obj['project'], obj['dataset'], create=False)
Experiment.expParamFromJson(experiment, obj, Configuration())
return experiment
def fromJson(obj, secuml_conf):
experiment = DescriptiveStatisticsExperiment(secuml_conf)
experiment.initExperiment(obj['project'], obj['dataset'], create=False)
Experiment.expParamFromJson(experiment, obj, None)
return experiment