class NeuralNetWork(Miner): def __init__(self): self.appliance = 'aircon' self.nnw = NNW(self.appliance) def mining(self, data): predict = self.predict(data['data']) return self.recommend(data['target'][self.appliance], predict) def predict(self, data): data = np.array([data]).astype(np.float32) return self.nnw.predict(data)[0] def recommend(self, current, predict): if predict is not None and current != predict: return [{'appliance': self.appliance, 'method': predict}] else: return []
class NeuralNetWork(Miner): def __init__(self): self.appliance = 'ceilinglight' self.nnw = NNW(self.appliance) def mining(self, data): predict = self.predict(data['data']) return self.recommend(data['target'][self.appliance], predict) def predict(self, data): data = np.array([data]).astype(np.float32) return self.nnw.predict(data)[0] def recommend(self, current, predict): if predict is not None and current != predict: return [{'appliance': self.appliance, 'method': predict}] else: return []
def __init__(self): self.appliance = 'ceilinglight' self.nnw = NNW(self.appliance)
def __init__(self): self.appliance = 'viera' self.nnw = NNW(self.appliance)
def __init__(self): self.appliance = 'aircon' self.nnw = NNW(self.appliance)
def __init__(self): self.appliance = 'curtain' self.nnw = NNW(self.appliance)
def __init__(self): self.appliance = 'fan' self.nnw = NNW(self.appliance)