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Nowadays, despite the use of efficient LED lighting, lighting consumes a considerable amount of energy. To reduce the energy consumption, many office lighting systems are equipped with occupancy sensors. Since these sensors have a limited reliability in detecting presence, usually very conservative strategies are used such as keeping the lights on for fifteen minutes after the last detected presence...
Feature selection and inference through modeling are combined into one method based on a network that can be used to point out irrelevant, redundant and dependent features in the data. It is shown that this network method is efficient in terms of reducing the number of calculations for estimating the probabilities under different model assumptions by breaking the data into fractions. We prove that...
Feature selection and learning through selected features are the two steps that are generally taken in classification applications. Commonly, each of these tasks are dealt with separately. In this paper, we introduce a method that optimally combines feature selection and learning through feature-based models. Our proposed method implicitly removes redundant and irrelevant features as it searches through...
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