… We consider the XGBoost and LSTM as two baselines and also consider the SVM [29] and
… The result is shown in Table 5; we can find that XGBoost and LSTM neural network can …

… disease using IoT, cloud computing, XGBoost, and Bi-LSTM in … , are continuously collected
by IoT devices like smartwatches and … for machine learning, such as Bi-LSTM and XGBoost. …

… of Prophet xgboost LSTM by combining models. After testing on public data sets and grain
data sets, and comparing with other algorithms, such as SVR, prophet, xgboost and LSTM, the …

… [29] used three methods, including the LSTM, kNN, and … the LSTM method achieved the best
F1 score on the IoT device … both IoT device datasets and a higher F1 score on the other IoT …

… For the reason that XGBoost model is relatively simple, we choose it as a comparison of
no feature engineering. urn:x-wiley:20474954:media:ntw2bf00267:ntw2bf00267-math-0097 …

… of a DNN model for an IoT framework. In this sense, we … consumption prediction developed
for an IoT module (see also [… the LSTM DNN and the well-known algorithms XGBoost and RF …

… design of LSTM, a prominent time series forecasting model allows it to … It is regarded as an
effective strategy for analyzing data or … When dealing with long-term dependencies, LSTM was …

… (RBFNN), and LSTM models. Particularly, the LSTM model and the XGBoost model are proven
… It is evident that LSTM has shown to be a reasonable indicator of approximate data, while …

… models LSTM + Random Forest and LSTM + XGBoost have better … it is clear that the
LSTM model shows more incorrect predictions as compared to its hybrid form, called LSTM+XGBoost…

… of regression algorithms like LSTM, XGBoost and LightGBM. … After comparison it is concluded
that LSTM outperforms the … deep learning models namely LSTM, XgBoost, and LightGBM is …