def __init__(self, data_root, log_dir, seed, model_config, data_config):
super(SVR, self).__init__(data_root, log_dir, seed, model_config,
data_config)
# Instantiate model
svr_config = {
k: eval(v)
for k, v in model_config.items() if v == 'False' or v == 'True'
}
self.model = sklearn_SVR(**svr_config)
def __init__(self,
ref_spd,
target_spd,
averaging_prd,
coverage_threshold,
bw_model=0,
preprocess=True,
**sklearn_args):
CorrelBase.__init__(self,
ref_spd,
target_spd,
averaging_prd,
coverage_threshold,
preprocess=preprocess)
bw_models = [{
'kernel': 'rbf',
'C': 30,
'gamma': 0.01
}, {
'kernel': 'linear',
'C': 10
}]
self.model = sklearn_SVR(**{**bw_models[bw_model], **sklearn_args})
self.params = 'not run yet'