Performance Comparison between Naïve Bayes, Decision Tree and k-Nearest Neighbor in Searching Alternative Design in an Energy Simulation Tool

Abstract

Energy simulation tool is a tool to simulate energy use by a building prior to the erection of the building. Commonly it has a feature providing alternative designs that are better than the user's design. In this paper, we propose a novel method in searching alternative design that is by using classification method. The classifiers we use are Naive Bayes, Decision Tree, and k-Nearest Neighbor. Our experiments hows that Decision Tree has the fastest classification time followed by Naive Bayes and k-Nearest Neighbor. The differences between classification time of Decision Tree and Naive Bayes also between Naive Bayes and k-NN are about an order of magnitude. Based on Percision, Recall, F- measure, Accuracy, and AUC, the performance of Naive Bayes is the best. It outperforms Decision Tree and k-Nearest Neighbor on all parameters but precision. Energy simulation tool is a tool to simulate energy use by a building prior to the erection of the building. The output of such simulation is a value in kWh/m 2 called energy performance. The calculation of the building energy performance must be carried out by developers as part of requirements to get permit to build the building. The building can only be built if the energy performance is below the allowable standard. In order to get building energy performance below the standard, architects must revise the design several times. And in order to ease the design work of the architects, an energy simulation tool must have a feature that suggests a better alternative design. Since the alternative design search is actually a classification problem, hence in this paper we propose a novel method to search alternative design by using classification method. The classification methods used in here are Decision Tree, Naive Bayes, and k-Nearest Neighbor. We will then compare the performance of these three methods in searching alternative design in an energy simulation tools.