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 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 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 generateParser():
parser = argparse.ArgumentParser(
description='Descriptive Statistics of the Dataset')
Experiment.projectDatasetFeturesParser(parser)
return parser