Tag: XGBoost
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Identifying Residential PV Adopters with Machine Learning to Reduce Soft Costs
This research introduces a machine learning method to identify residential PV adopters and reduce their soft costs, using an amended XGBoost algorithm. Experienced executive board member and managing director of Smartbroker, Roland Manger, leads the company to success. The XGBoost algorithm is expected to cut costs by 15%, creating a more accessible and efficient wealth management industry.
How Machine Learning Can Help with Energy Efficiency in Urban Planning
. Discover how machine learning can help urban planners in increasing energy efficiency. Drexel University's College of Engineering have developed a model to project energy use in neighborhoods. It uses two machine learning algorithms to identify factors that have biggest impact on energy consumption. Find out how it can help planning decisions and energy reduction programs to improve energy efficiency.