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