def main(dataset, output, epsilon, capacity, width, kernel_type):
LOGGER.info("SVM Multiclass classifier")
LOGGER.info("Epsilon: %s" % epsilon)
LOGGER.info("Capacity: %s" % capacity)
LOGGER.info("Gaussian width: %s" % width)
# Get features
feats, labels = get_features_and_labels(LibSVMFile(dataset))
# Create kernel
try:
kernel = KERNELS[kernel_type](feats, width)
except KeyError:
LOGGER.error("Kernel %s not available. try Gaussian or Linear" % kernel_type)
# Initialize and train Multiclass SVM
svm = MulticlassLibSVM(capacity, kernel, labels)
svm.set_epsilon(epsilon)
with track_execution():
svm.train()
# Serialize to file
writable_file = SerializableHdf5File(output, 'w')
with closing(writable_file):
svm.save_serializable(writable_file)
LOGGER.info("Serialized classifier saved in: '%s'" % output)
