Results 21 to 30 of about 29,456 (261)
Fast TreeSHAP: Accelerating SHAP Value Computation for Trees
CoRR, 2021 22 pages (including 10-page appendix), 2 ...
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SHAP values for Explaining CNN-based Text Classification Models
CoRR, 2020 17 pages, 5 ...
Wei Zhao +3 more
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The Relationship between Lifestyle Factors and Depression: a Cross-sectional Study of Community Populations [PDF]
Zhongguo quanke yixueBackground Depression is an increasingly serious public health problem worldwide, and the relationship between depression diagnosed using structured clinical interview for DSM-Ⅳ personality disorders according to the Diagnostic and Statistical Manual of ...
ZHAO Ziqi, LIU Mingyue, WANG Nan, LUO Zhenghao, CHEN Xinyang, LI Zheng, ZHANG Shangmingzhu, ZHANG Haoruo, CHEN Jiaqi, ZHENG Yizhan, ZHANG Xiujun, WU Jianhui
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SHAP values examples for two different predictions
, 2023 These SHAP values tensors are examples of the results we can obtain with "linear_model_predictions.ipynb". They have been calculated from precipitation and temperature anomalies predictions 5-6 weeks ahead, for the years 2012 and 2016. These files can be added respectively in the repository you can find on GitHub "https://github.com/AlexandreRebiere ...
Rebière, Alexandre, Gentine, Pierre
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Bir Makine Öğrenimi Uygulaması: G7 Ülkelerinde Finansal Kriz Tahminleme
Ekonomi, Politika & Finans Araştırmaları DergisiBu çalışmada, 1870-2020 dönemi için G7 ülkelerine ait finansal ve makroekonomik veriler kullanılarak sistemik bankacılık kriz tahmininde XGBoost tabanlı bir model geliştirilmiştir.
Mert Ural, Merve Mert Sarıtaş
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Shap-Select: Lightweight Feature Selection Using SHAP Values and Regression
CoRRFeature selection is an essential process in machine learning, especially when dealing with high-dimensional datasets. It helps reduce the complexity of machine learning models, improve performance, mitigate overfitting, and decrease computation time. This paper presents a novel feature selection framework, shap-select.
Egor Kraev +3 more
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PDD-SHAP: Fast Approximations for Shapley Values using Functional Decomposition
CoRR, 2022 Because of their strong theoretical properties, Shapley values have become very popular as a way to explain predictions made by black box models. Unfortuately, most existing techniques to compute Shapley values are computationally very expensive. We propose PDD-SHAP, an algorithm that uses an ANOVA-based functional decomposition model to approximate ...
Arne Gevaert, Yvan Saeys
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New Trends in Computer Sciences, 2023 Understanding the factors that affect Key Performance Indicators (KPIs) and how they affect them is frequently important in sectors where data and data science are crucial.
Serap Ergün
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Arterial Spin‐Labeling MRI at the Cortical‐CSF Interface: A Novel Biomarker in Alzheimer Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background/Objective Arterial spin‐labeling (ASL) MRI can measure perfusion signal adjacent to CSF spaces and may provide information regarding CSF‐adjacent water transport physiology. We developed an automated pipeline to extract cortical‐CSF interface (IF) perfusion for comparison between Alzheimer disease (AD) and cognitively normal ...
Mona Asghariahmadabad +22 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP‐A) is an inflammatory central nervous system disorder with variable outcomes. Relapse occurs in a subset of patients, but early predictors remain unclear. We aimed to identify admission‐available features associated with 1‐year recurrence and develop an interpretable ...
Qingting Hong +10 more
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