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Conditional feature importance for mixed data
AStA Advances in Statistical Analysis, 2023 AbstractDespite the popularity of feature importance (FI) measures in interpretable machine learning, the statistical adequacy of these methods is rarely discussed. From a statistical perspective, a major distinction is between analysing a variable’s importance before and after adjusting for covariates—i.e., between marginal and conditional measures ...
Kristin Blesch +2 more
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Combined Feature Selection Scheme for Banking Modeling
Финансы: теория и практика, 2023 Machine learning methods have been successful in various aspects of bank lending. Banks have accumulated huge amounts of data about borrowers over the years of application.
S. V. Afanasyev +3 more
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Predicting coastal algal blooms with environmental factors by machine learning methods
Ecological Indicators, 2021 Harmful algal blooms are a major type of marine disaster that endangers the marine ecological environment and human health. Since the algal bloom is a complex nonlinear process with time characteristics, traditional statistical methods often cannot ...
Peixuan Yu +3 more
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Measuring Feature Importance of Convolutional Neural Networks
IEEE Access, 2020 Convolutional neural networks have demonstrated powerful abilities to achieve state-of-the-art results in many classification tasks, while the interpretability and reliability of these complicated models are also a non-negligible problem.
Xiaohang Zhang, Jiuyi Gao
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The Feature Importance Ranking Measure [PDF]
, 2009 15 pages, 3 figures. to appear in the Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD ...
Alexander Zien +3 more
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The determinants of health assessment in the United States: A supervised learning approach
Healthcare Analytics, 2022 In this article, we exploit a large dataset of surveys to answer a simple questions: which factors drive good (or bad) health? Using a set of 14 very diverse predictors (both socioeconomic and physiological), we perform sets of supervised learning tasks ...
Guillaume Coqueret
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Random Forest and Feature Importance Measures for Discriminating the Most Influential Environmental Factors in Predicting Cardiovascular and Respiratory Diseases [PDF]
International Journal of Environmental Research and Public HealthSalvatore Grimaldi +2 more
exaly +2 more sources
Frontiers in Big DataIntroductionStudies from different parts of the world have shown that some comorbidities are associated with fatal cases of COVID-19. However, the prevalence rates of comorbidities are different around the world, therefore, their contribution to COVID-19
Jorge Méndez-Astudillo
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Energy Conservation in Wireless Sensor Networks Using Partly-Informed Sparse Autoencoder
IEEE Access, 2019 The energy in wireless sensor networks is considered a scarce commodity, especially in scenarios where it is difficult or impossible to provide supplementary energy sources once the initially available energy is used up.
Babajide O. Ayinde, Abdulaziz Y. Barnawi
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