Using an ensemble machine learning methodology-Bagging to predict occupants' thermal comfort in buildings

In our case study, the Bagging model's R2 for TS, PMV, ET* and SET* were 0.4986, 0.9892, 0.9920 and 0.9900, respectively. It shows higher accuracy than SVM and ANN models in thermal perception prediction and outperforms the classical PMV index in TS prediction. Results indicate the proposed Bagging model's prediction performance is reliable and is highly accurate to predict the thermal perception.