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IOT Based Environment Comfort Level Prediction Model Using Ensemble Learning
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Predicting indoor environment comfort through machine learning algorithm is considered as an important research topic nowadays. People spend most of the time inside the building by doing some kitchen work, reading, watching TV, work in office building, learning in classroom, patients in hospital, workers in industry etc. Environment should be comfortable for healthy living. Thus, predicting the comfort level of the environment is necessary for keeping good health and wellbeing. Machine learning algorithm play an important role in prediction model. This paper focus on predicting the comfort of environment using machine learning classifier model. This model is used to train and improve the robustness of the model. This ensemble model is applied to reduce bias factor to enhance the stability and accuracy of the result.
Keywords
Ensemble, Confusion Matrix, Boosting, Machine Learning, Comfort Level.
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