resource/model_param/libsvmnusvr_v1.py (8 lines of code) (raw):
model_type = "LIBSVMNUSVR"
model_param_dict = {
# ==== preprocess: normalize each feature ==== #
# 'norm_type': 'none', # default: do nothing
'norm_type': 'clip_0to1', # rescale to within [0, 1]
# 'norm_type': 'clip_minus1to1', # rescale to within [-1, 1]
# 'norm_type': 'normalize', # rescale to mean zero and std one
# ==== postprocess: clip final quality score ==== #
# 'score_clip': None, # default: do nothing
'score_clip': [0.0, 100.0], # clip to within [0, 100]
# ==== libsvmnusvr parameters ==== #
# 'gamma': 0.0, # default
'gamma': 0.1, # vmafv1
# 'C': 1.0, # default
'C': 3.1, # vmafv1
# 'nu': 0.5, # default
'nu': 0.9, # vmafv1
}