def _train_svr(mat_files, out_file, C=1000, gamma=0.001, epsilon=0.01):
"""
Trains SVR with the given parameters
"""
peptides, signals = _get_peptides_signals(mat_files)
model = SvrBlockade()
model.train(peptides, signals, C, gamma, epsilon)
store_model(model, out_file)
def _train_svr(mat_files, out_file, C=1000, gamma=0.001, epsilon=0.01):
"""
Trains SVR with the given parameters
"""
peptides, signals = _get_peptides_signals(mat_files)
model = SvrBlockade()
model.train(peptides, signals, C, gamma, epsilon)
store_model(model, out_file)
def load_model(filename):
if filename == "-":
return MvBlockade()
dump = pickle.load(open(filename, "rb"))
if dump.name == SvrBlockade().name:
model = SvrBlockade()
elif dump.name == RandomForestBlockade().name:
model = RandomForestBlockade()
model.load_from_dump(dump)
return model
def load_model(filename):
if filename == "-":
return MvBlockade()
dump = pickle.load(open(filename, "rb"))
if dump.name == SvrBlockade().name:
model = SvrBlockade()
elif dump.name == RandomForestBlockade().name:
model = RandomForestBlockade()
model.load_from_dump(dump)
return model
