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Using Decision Trees to Predict Forest Stand Height and Canopy Cover from LANDSAT and LIDAR Data.

, , , and . EnviroInfo, page 125-133. Shaker Verlag, Aachen, (2006)

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Representing bioinformatics datatypes using the OntoDT ontology., , and . ICBO, volume 1515 of CEUR Workshop Proceedings,, (2015)OPTION: optimization algorithm benchmarking ontology., , , , , and . GECCO Companion, page 239-240. ACM, (2021)Multi-criteria Modelling Approach for Ambient Assisted Coaching of Senior Adults., , , , , , , and . KEOD, page 87-93. ScitePress, (2019)iSOUP-SymRF: Symbolic Feature Ranking with Random Forests in Online Multi-target Regression., , and . DS, volume 14276 of Lecture Notes in Computer Science, page 48-63. Springer, (2023)Combining Bagging and Random Subspaces to Create Better Ensembles., and . IDA, volume 4723 of Lecture Notes in Computer Science, page 118-129. Springer, (2007)Estimating vegetation height and canopy cover from remotely sensed data with machine learning., , , , and . Ecol. Informatics, 5 (4): 256-266 (2010)Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms., , , , , and . EvoApplications@EvoStar, volume 13989 of Lecture Notes in Computer Science, page 253-268. Springer, (2023)The Influence of Window Size on the Prediction Power in the Case of Absenteeism Prediction from Timesheet Data., and . MIPRO, page 193-198. IEEE, (2021)OntoDM: An Ontology of Data Mining., , and . ICDM Workshops, page 752-760. IEEE Computer Society, (2008)Utilizing Hierarchies in Tree-Based Online Structured Output Prediction., , and . DS, volume 11828 of Lecture Notes in Computer Science, page 87-95. Springer, (2019)