arg3: + path to file containing the testing dataset (arg1 = 1)
+ percentage of the training dataset in the input file
arg4: + True: drawing hyperboxes during the training process
+ False: no drawing
arg5: + Maximum size of hyperboxes (teta, default: 1)
arg6: + The minimum value of maximum size of hyperboxes (teta_min: default = teta)
arg7: + gamma value (default: 1)
arg8: operation used to compute membership value: 'min' or 'prod' (default: 'min')
arg9: + do normalization of datasets or not? True: Normilize, False: No normalize (default: True)
arg10: + range of input values after normalization (default: [0, 1])
"""
# Init default parameters
if len(sys.argv) < 5:
isDraw = False
else:
isDraw = string_to_boolean(sys.argv[4])
if len(sys.argv) < 6:
teta = 1
else:
teta = float(sys.argv[5])
if len(sys.argv) < 7:
teta_min = teta
else:
teta_min = float(sys.argv[6])
if len(sys.argv) < 8:
gamma = 1
else:
gamma = float(sys.argv[7])
arg2: path to file containing the training dataset (arg1 = 1) or both training and testing datasets (arg1 = 2)
arg3: + path to file containing the testing dataset (arg1 = 1)
+ percentage of the training dataset in the input file
arg4: + path to file containing the validation dataset
arg5: + True: drawing hyperboxes during the training process
+ False: no drawing
arg6: + Maximum size of hyperboxes (teta, default: 1)
arg7: + gamma value (default: 1)
arg8: + do normalization of datasets or not? True: Normilize, False: No normalize (default: True)
arg9: + range of input values after normalization (default: [0, 1])
"""
# Init default parameters
if len(sys.argv) < 6:
isDraw = False
else:
isDraw = string_to_boolean(sys.argv[5])
if len(sys.argv) < 7:
teta = 1
else:
teta = float(sys.argv[6])
if len(sys.argv) < 8:
gamma = 1
else:
gamma = float(sys.argv[7])
if len(sys.argv) < 9:
isNorm = True
else:
isNorm = string_to_boolean(sys.argv[8])
bthres = float(sys.argv[8])
if len(sys.argv) < 10:
simil = 'mid'
else:
simil = sys.argv[9]
if len(sys.argv) < 11:
oper = 'min'
else:
oper = sys.argv[10]
if len(sys.argv) < 12:
isNorm = True
else:
isNorm = string_to_boolean(sys.argv[11])
if len(sys.argv) < 13:
norm_range = [0, 1]
else:
norm_range = ast.literal_eval(sys.argv[12])
if len(sys.argv) < 14:
sing = 'max'
else:
sing = sys.argv[13]
if len(sys.argv) < 15:
typeOfSplit = 0
else:
typeOfSplit = int(sys.argv[14])
bthres_min = float(sys.argv[8])
if len(sys.argv) < 10:
simil = 'mid'
else:
simil = sys.argv[9]
if len(sys.argv) < 11:
oper = 'min'
else:
oper = sys.argv[10]
if len(sys.argv) < 12:
isNorm = True
else:
isNorm = string_to_boolean(sys.argv[11])
if len(sys.argv) < 13:
norm_range = [0, 1]
else:
norm_range = ast.literal_eval(sys.argv[12])
if len(sys.argv) < 14:
sing = 'max'
else:
sing = sys.argv[13]
if len(sys.argv) < 15:
typeOfSplit = 0
else:
typeOfSplit = int(sys.argv[14])
if len(sys.argv) < 8:
max_features = "auto"
else:
try:
max_features = int(sys.argv[7])
except:
try:
max_features = float(sys.argv[7])
except:
max_features = sys.argv[7]
if len(sys.argv) < 9:
bootstrap_sample = True
else:
bootstrap_sample = string_to_boolean(sys.argv[8])
if len(sys.argv) < 10:
class_sample_rate = 0.5
else:
class_sample_rate = float(sys.argv[9])
if len(sys.argv) < 11:
bootstrap_feature = True
else:
bootstrap_feature = string_to_boolean(sys.argv[10])
if len(sys.argv) < 12:
n_jobs = 1
else:
try:
