def save(self, path_file):
""" Save the model paremeters of the model (.params) and Compress
them into a zip file
"""
# Ensuring the file has the proper name
folder_name = os.path.dirname(path_file) + '/'
file_name = os.path.basename(path_file)
# Checking if the folder is accessible
if not os.access(folder_name, os.W_OK):
error_msg = '{} is not an accessible directory.'.format(
folder_name)
raise OSError(error_msg)
# Delete the C++ object before saving
del self.model
# Saving the model
super(SurvivalSVMModel, self).save(path_file)
# Re-introduce the C++ object
self.model = _SVMModel(self.kernel_type, self.scale, self.offset,
self.degree)
self.load_properties()
def load(self, path_file):
""" Load the model parameters from a zip file into a C++ external
model
"""
# Loading the model
super(SurvivalSVMModel, self).load(path_file)
# Re-introduce the C++ object
self.model = _SVMModel(self.kernel_type, self.scale, self.offset,
self.degree)
self.load_properties()
def __init__(self,
kernel="linear",
scale=1.,
offset=0.,
degree=1.,
auto_scaler=True):
# Ensuring that the provided kernel is available
valid_kernel = [key for key in KERNELS.keys() \
if kernel.lower().replace('_', ' ') in key.lower().replace('_', ' ')]
if len(valid_kernel) == 0:
raise NotImplementedError(
'{} is not a valid kernel function.'.format(kernel))
else:
kernel_type = KERNELS[valid_kernel[0]]
kernel = valid_kernel[0]
# Checking the kernel parameters
if not (degree >= 0. and
(isinstance(degree, float) or isinstance(degree, int))):
error = "degree parameter is not valid. degree is a >= 0 value"
raise ValueError(error)
if not (isinstance(scale, float) or isinstance(scale, int)):
error = "scale parameter is not valid."
raise ValueError(error)
if not (isinstance(offset, float) or isinstance(offset, int)):
error = "offset parameter is not valid."
raise ValueError(error)
# Saving the attributes
self.kernel = kernel
self.kernel_type = kernel_type
self.scale = scale
self.offset = offset
self.degree = degree
# Initializing the C++ object
self.model = _SVMModel(self.kernel_type, self.scale, self.offset,
self.degree)
# Initializing the elements from BaseModel
super(SurvivalSVMModel, self).__init__(auto_scaler)