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)