首页|Findings on Machine Learning Detailed by Investigators at University of Copenhag en (Markov-switching Decision Trees)
Findings on Machine Learning Detailed by Investigators at University of Copenhag en (Markov-switching Decision Trees)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Machine Learning are pre sented in a new report. According to news reporting from Copenhagen, Denmark, by NewsRx journalists, research stated, "Decision trees constitute a simple yet po werful and interpretable machine learning tool. While tree-based methods are des igned only for cross-sectional data, we propose an approach that combines decisi on trees with time series modeling and thereby bridges the gap between machine l earning and statistics." Financial support for this research came from Universitt Bielefeld (3146). The news correspondents obtained a quote from the research from the University o f Copenhagen, "In particular, we combine decision trees with hidden Markov model s where, for any time point, an underlying (hidden) Markov chain selects the tre e that generates the corresponding observation. We propose an estimation approac h that is based on the expectation-maximisation algorithm and assess its feasibi lity in simulation experiments. In our real-data application, we use eight seaso ns of National Football League (NFL) data to predict play calls conditional on c ovariates, such as the current quarter and the score, where the model's states c an be linked to the teams' strategies."
CopenhagenDenmarkEuropeCyborgsEm erging TechnologiesMachine LearningUniversity of Copenhagen
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