def set_optimization_params(opt):
params = {}
for key, item in opt.items():
# checks if the item is a list with numbers (ignores cv and n_jobs params)
if isinstance(item, list) and (len(item) == 3) and assert_number(item):
# create linear space for each parameter to be tuned
params[key] = np.linspace(item[0], item[1], num=item[2], endpoint=True)
elif isinstance(item, list) and assert_string(item):
params[key] = item
return params
def set_optimization_params(opt):
params = {}
for key, item in opt.items():
# checks if the item is a list with numbers (ignores cv and n_jobs params)
# if isinstance(item, list) and (len(item) == 3) and assert_number(item):
if isinstance(item, list) and assert_number(item):
# create linear space for each parameter to be tuned
params[key] = item
#params[key] = np.linspace(item[0], item[1], num=item[2], endpoint=True)
elif isinstance(item, list) and assert_string(item):
# print key, item
params[key] = item
return params