def restoreTree(moduleName):
"""
If you have decision rules, then this function enables you to load a built chefboost model. You can then call prediction.
Parameters:
moduleName (string): you should pass outputs/rules/rules if you want to restore outputs/rules/rules.py
Returns:
built chefboost model
"""
return functions.restoreTree(moduleName)
def load_model(file_name="model.pkl"):
f = open('outputs/rules/'+file_name, 'rb')
model = pickle.load(f)
#restore modules from its references
modules = []
for model_name in model["trees"]:
module = functions.restoreTree(model_name)
modules.append(module)
model["trees"] = modules
return model
def load_model(file_name="model.pkl"):
"""
Parameters:
file_name (string): exact path of the target saved model
Returns:
built chefboost model
"""
f = open('outputs/rules/' + file_name, 'rb')
model = pickle.load(f)
#restore modules from its references
modules = []
for model_name in model["trees"]:
module = functions.restoreTree(model_name)
modules.append(module)
model["trees"] = modules
return model
def restoreTree(moduleName): return functions.restoreTree(moduleName)
