Sample-selection-adjusted random forests

Cook, Jonathan

doi:10.1007/s41060-022-00337-w

Cited by 3 publications

(2 citation statements)

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“…The possibility of selection bias and the lack of data granularity, due to the administrative nature of this database, could have impacted bRF predictability; furthermore, the currently available software for random forest methodology does not support the recently developed sample-selection-adjusted models. 35 Inconsistent coding practices among institutions may have resulted in over- or underestimations of events, although robust quality control measures were in place to minimize these discrepancies. In our assessment of the secondary end points, some ICD codes were not helpful to distinguish between comorbidities and complications; thus, the rate of complications is likely to be overestimated given the existing limitations of the administrative databases.…”

Section: Discussionmentioning

confidence: 99%

Predictors of outcomes in patients with obesity following mitral valve surgery

et al. 2023

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Section: Discussionmentioning

confidence: 99%

Predictors of outcomes in patients with obesity following mitral valve surgery

et al. 2023

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“…This adjustment makes the population forecast more accurate. Also caution against using inverse probability weighting when analyzing selected samples [3]. In this context, research and discussion are carried out from the aspects of natural resource utilization, ecological environment supervision, social organization management, etc.…”

Section: Introductionmentioning

confidence: 99%

Nature Conservation Environment Based on Public Participation of Random Forests

2023

NEP

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With the development of social economy, the public's awareness of participating in the natural protection of the environment has gradually increased, and a certain organizational structure and interest expression mechanism have gradually formed in the natural protection of the environment. The public's participation in natural environment protection is also increasingly concerned by government departments, social organizations and enterprises. Based on the random forest model, combined with public participation activities and management practice experience, this paper explores the problems and solutions of public participation in natural protection environment. The results show that: in the questionnaire survey of public environmental awareness, 164 people said "very important", 92.1%; Thirteen respondents thought it was "important", 7.3% of all respondents. There are 177 items in total, about 99.4% of all respondents. This shows that most people are still aware of environmental protection, but lack guidance.

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A hybrid forecasting method for cooling load in large public buildings based on improved long short term memory

Liu

Feng

et al. 2023

Journal of Building Engineering

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Sample-selection-adjusted random forests

Cited by 3 publications

References 20 publications

Predictors of outcomes in patients with obesity following mitral valve surgery

Predictors of outcomes in patients with obesity following mitral valve surgery

Nature Conservation Environment Based on Public Participation of Random Forests

A hybrid forecasting method for cooling load in large public buildings based on improved long short term memory

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