2021
DOI: 10.1111/tgis.12770
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Transferring decision boundaries onto a geographic space: Agent rules extracted from movement data using classification trees

Abstract: We leverage applied machine learning to determine which environmental features are best associated with the “moving” behaviour(s) of a troop of olive baboons (Papio anubis; collared with GPS trackers at Mpala Research Centre, Kenya). Specifically, we develop a behaviour‐selection surface informed by classification trees trained using movement trajectories and remotely sensed environmental features. Atop this surface, we simulate agent movement towards set destinations, constrained by the relative extent to whi… Show more

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“…After pre-processing the data and processing them in a continuous and temporal manner, the DT software was used to classify the students in each course and generate DTs and decision rules [16]. The generated decision rules describe the association and if then relationship between the overall learning behavior and learning outcomes of the students taking the course, and for the teachers, they can know which learning patterns the overall students have for the course, and further infer which learning patterns the students in the high or low scoring groups may have, and this supporting decision information can be used as a reference for the teachers to implement future teaching The decision information can be used as a reference for teachers to implement teaching strategies and teaching aids in the future [17][18].…”
Section: Generation Analysis and Collation Of Dt Classificationmentioning
confidence: 99%
“…After pre-processing the data and processing them in a continuous and temporal manner, the DT software was used to classify the students in each course and generate DTs and decision rules [16]. The generated decision rules describe the association and if then relationship between the overall learning behavior and learning outcomes of the students taking the course, and for the teachers, they can know which learning patterns the overall students have for the course, and further infer which learning patterns the students in the high or low scoring groups may have, and this supporting decision information can be used as a reference for the teachers to implement future teaching The decision information can be used as a reference for teachers to implement teaching strategies and teaching aids in the future [17][18].…”
Section: Generation Analysis and Collation Of Dt Classificationmentioning
confidence: 99%