# SecuML # Copyright (C) 2016-2019 ANSSI # # SecuML is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # SecuML is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with SecuML. If not, see <http://www.gnu.org/licenses/>. from secuml.core.conf import register_submodules from . import algos register_submodules(algos, algos.get_factory())
# SecuML # Copyright (C) 2016-2018 ANSSI # # SecuML is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # SecuML is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with SecuML. If not, see <http://www.gnu.org/licenses/>. from . import strategies from secuml.core.conf import register_submodules register_submodules(strategies, strategies.get_factory())
name += self.classifier_conf.get_exp_name()
name += self.test_conf.get_exp_name()
return name
def fields_to_export(self):
return [('classifier_conf', exportFieldMethod.obj),
('test_conf', exportFieldMethod.obj)]
@staticmethod
def gen_parser(parser):
TestConf.gen_parser(parser)
@staticmethod
def from_args(args, logger):
classifier_conf = classifiers.get_factory().from_args(
args.model_class, args, logger)
test_conf = test.get_factory().from_args(args.validation_mode, args,
logger)
return ClassificationConf(classifier_conf, test_conf, logger)
def from_json(conf_json, logger):
classifier_conf = classifiers.get_factory().from_json(
conf_json['classifier_conf'], logger)
test_conf = test.get_factory().from_json(conf_json['test_conf'],
logger)
return ClassificationConf(classifier_conf, test_conf, logger)
register_submodules(classifiers, classifiers.get_factory())
register_submodules(test, test.get_factory())
return None
factory = objective_func.get_factory()
obj_func_conf = factory.from_json(obj['objective_func'], logger)
return OptimConf(obj['num_folds'], obj['n_jobs'], obj_func_conf,
logger)
@staticmethod
def from_args(args, logger):
factory = objective_func.get_factory()
if args.multiclass:
obj_func_conf = factory.from_args('Accuracy', args, logger)
else:
obj_func_conf = factory.from_args(args.objective_func, args,
logger)
return OptimConf(args.num_folds, args.n_jobs, obj_func_conf, logger)
@staticmethod
def get_default(num_folds, n_jobs, multiclass, logger):
if num_folds is None:
num_folds = 4
if n_jobs is None:
n_jobs = 1
if multiclass:
scoring = AccuracyConf
else:
scoring = RocAucConf
return OptimConf(num_folds, n_jobs, scoring(logger), logger)
register_submodules(objective_func, objective_func.get_factory())