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