print("config_file -- yaml filepath containing all parameters")
exit(1)
config_file = sys.argv[1]
my_params = yaml.load(open(config_file))
feature_types = my_params.get('feature_types').split(',')
dims = my_params.get('feature_dims').split(',')
feature_dims = [int(x) for x in dims]
feature_files = [
'../../features/' + x
for x in my_params.get('feature_files').split(',')
]
use_balanced_data = str2bool(my_params.get('balanced'))
factor = int(my_params.get('factor'))
train_list = my_params.get('train')
val_list = my_params.get('val')
test_list = my_params.get('test')
features = Features(feature_types, feature_dims, feature_files)
features.load_train(train_list)
features.load_val(val_list)
features.load_test(test_list)
features.get_balanced_data(factor)
SVC_model = Model_Train(features, SVC())
for g in ParameterGrid(grid):
SVC_model.train(g)
print(SVC_model.validate(), g)
SVC_model.train_cv(grid, use_balanced_data)
SVC_model.test()
SVC_model.persist_test_result('EF')
