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General Sewer Deterioration Model Using Random Forest
2019 IEEE Symposium Series on Computational Intelligence (SSCI), 2019Collapse of sewers can induce significant damage to roads and buildings, resulting in large economical costs. Therefore, utilities wish to repair or replace the sewers before they collapse. In order to investigate if a sewer needs maintenance or replacement it can be inspected with Closed Circuit Television (CCTV), but as CCTV inspection is very ...
Bolette Dybkjær Hansen +5 more
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Preventing customer churn by using random forests modeling
2008 IEEE International Conference on Information Reuse and Integration, 2008In this paper, we use the improved balanced random forests(IBRF) to predict the customer churn, while integrating a sampling technique and cost-sensitive learning into the standard random forests to achieve a better performance than most existing algorithms.
Weiyun Ying +3 more
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Multigenic Modeling of Complex Disease by Random Forests
2010The genetics and heredity of complex human traits have been studied for over a century. Many genes have been implicated in these complex traits. Genome-wide association studies (GWAS) were designed to investigate the association between common genetic variation and complex human traits using high-throughput platforms that measured hundreds of thousands
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Random forests and the data sparseness problem in language modeling
Computer Speech & Language, 2007Abstract Language modeling is the problem of predicting words based on histories containing words already hypothesized. Two key aspects of language modeling are effective history equivalence classification and robust probability estimation. The solution of these aspects is hindered by the data sparseness problem.
Peng Xu, Frederick Jelinek
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A Random Forest Concentration Detection Model for Short Video
2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), 2018The detection of concentration is widely used in the fields of education, advertising, and fatigue driving. In order to improve the objectivity, convenience and accuracy of concentration detection, this paper proposes a scheme for using machine learning to detect the concentration of short video. In this scheme, since the eye movement features are used
Jiao Zhang +3 more
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Measuring regional effects of model inputs with random Forest
Communications in Statistics - Simulation and Computation, 2018In many disciplines involving high-dimensional data, permutation variable importance measure (PVIM) based on random forest is widely used for importance ranking of model inputs.
Jingwen Song +2 more
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A Random Forest Model for Mental Disorders Diagnostic Systems
2016Data mining has established new applications in medicine over the last few years. Using mental disorders diagnostic systems, data possession, and data analysis has been of enormous succor for clinicians to recognize diseases more precisely, especially when dealing with overlapping mental symptoms.
Horeya Abou-Warda +3 more
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Model of Gradient Boosting Random Forest Prediction
2022 IEEE International Conference on Networking, Sensing and Control (ICNSC), 2022Zhidong Zhang, Xiubin Zhu, Ding Liu
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Explainable Optimal Random Forest Model with Conversational Interface
Engineering Applications of Artificial Intelligence, 2023Caroline Mary M. +2 more
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Random forest-based nowcast model for rainfall
Earth Science Informatics, 2023Nita H. Shah +2 more
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