Random forest(RF) algorithm has been successfully applied to high-dimensional neuroimaging data for feature reduction and also has been applied to classify the clinical label of a subject using single or multi-modal neuroimaging datasets. Our aim was to review the studies where RF was applied to ...
Mashayekhi, M. and Gras, R. (2015) Rule Extraction from Random Forest: The RF + HC Methods. Advances in Artificial Intelligence, Canberra, 30 November-4 De- cember 2015, 223-237.M. Mashayekhi, R. Gras, Rule extraction from random forest: The RF+HC methods, in: Proceedings of the ...
the model factors should be selected comprehensively. The random forest (RF) algorithm is a suitable for handling the selection and classification work and is commonly used in different fields37,38,39. In this study, the RF model is built to screen out the core factors. ...
Random Survival Forests for High-:随机生存森林高- 热度: 相关推荐 METHODOLOGYARTICLEOpenAccess Theparametersensitivityofrandomforests BarbaraF.F.Huang 1 andPaulC.Boutros 1,2,3,4* Abstract Background:TheRandomForest(RF)algorithmforsupervisedmachinelearningisanensemblelearningmethod widelyusedinscienceandma...
A Random Forest machine learning algorithm is applied, and results compared with previously established expert-driven maps. Optimal predictive conditions for the algorithm are observed for (i) a forest size superior to a hundred trees, (ii) a training dataset larger than 10%, and (iii) a ...
Random Forest is an ensemble, supervised machine learning algorithm. An ensemble generates many classifiers and combines their results by majority voting. Random forest uses decision tree as base classifier. In decision tree induction, an attribute split/evaluation measure is used to decide the best ...
Random forest RF is an ensemble learning algorithm designed to improve the regression and classification of trees by integrating a wide range of decision-making trees68. RF is an effective method for managing data vagueness and complexity and has been successfully used to evaluate many complex datase...
Aiming to address the problem of strong randomness and strong temporal correlations in wind power prediction (WPP), a new framework for WPP based on RF-WOA-VMD and BiGRU optimized by an attention mechanism is proposed. Firstly, the random forest algorithm (RF) is adopted to screen the ...
A Random Forest-Based Self-training Algorithm for Study Status Prediction at the Program Level: minSemi-RFSelf-trainingRandom forestTri-trainingEducational data miningStudy status predictionEducational data mining aims to provide useful knowledge hidden in educational data for better educational decision ...
The MSI-based RF algorithm inside the GEE performed paddy rice fields classification in a very short time. Thus, high-performance computing resources like GEE facilitate quick and rapid mapping of paddy rice planting areas at a large scale1,6. Future studies of paddy rice mapping under similar ...