15 papers · ranked by Valyu relevance
Rory Mitchell, Eibe Frank, Geoffrey Holmes, Alberto Cano
SHapley Additive exPlanation (SHAP) values ([24]) provide a game theoretic interpretation of the predictions of machine learning models based on Shapley values ([35]). While exact calculation of SHAP values is computationally intractable in general, a recursive polynomial-time algorithm called TreeShap ([23]) is…
Saeid Saberi, Hamid Nasiri, Omid Ghorbani, Michael I. Friswell + 3 more
'Saullo G. P. Castro' 'Enrique Casarejos' 'Fernando Gomes de Souza Junior'] Material properties, geometrical dimensions, and environmental conditions can greatly influence the characteristics of bistable composite laminates. In the current work, to understand how each input feature contributes to the curvatures of the…
Hyeon-Seok Kim, Do-Hyeon Kim, Sun-Yong Choi, Feier Chen
The Baltic Dry Index (BDI) is a critical benchmark for assessing freight rates and chartering activity in the global shipping market. This study forecasts the BDI using diverse financial data, including commodities, currencies, stock markets, and volatility indices. Unlike previous research, our approach integrates…
Viswan Vimbi, Noushath Shaffi, Mufti Mahmud
Explainable artificial intelligence (XAI) has gained much interest in recent years for its ability to explain the complex decision-making process of machine learning (ML) and deep learning (DL) models. The Local Interpretable Model-agnostic Explanations (LIME) and Shaply Additive exPlanation (SHAP) frameworks have…
Honglin Song, Yutao Li, Xiaofeng Zou, Ping Hu + 1 more
This study adopts a new approach, SHapley Additive exPlanation (SHAP), to diagnose the table tennis matches based on a hybrid algorithm, namely Long Short-Term Memory-Back Propagation Neural Network (LSTM-BPNN). 100 male singles competitions (8535 rallies) from 2019 to 2022 are analyzed by a hybrid technical-tactical…
Ramtin Zargari Marandi, Yoshihiro Yamanishi
ExplaineR package was developed using the R programming language (4.1.3) based on popular and well-documented R packages including mlr3 (0.14.0) (), CVMS (1.3.4) (), and iml (0.11.0) (). ExplaineR package has been published at the Comprehensive R Archive Network (CRAN). The analytical foundation of the package is based…
Kyungtae Lee, Mukil V. Ayyasamy, Yangfeng Ji, Prasanna V. Balachandran
'Prasanna V. Balachandran'] We demonstrate the capabilities of two model-agnostic local post-hoc model interpretability methods, namely breakDown (BD) and shapley (SHAP), to explain the predictions of a black-box classification learning model that establishes a quantitative relationship between chemical composition and…
Ahmad A. Hanani, Turker Berk Donmez, Mustafa Kutlu, Mohammed Mansour
Recurrence prediction in well-differentiated thyroid cancer remains a clinical challenge, necessitating more accurate and interpretable predictive models. This study investigates the use of a supervised CatBoost classifier to predict recurrence in well-differentiated thyroid cancer patients, comparing its performance…
Tomohiro Ishibashi, Akio Onogi
Mapping quantitative trait loci (QTLs) is one of the major goals of quantitative genetics; however, identifying the interactions between QTLs (i.e., epistasis) remains challenging. Recently developed machine learning methods, such as deep learning and gradient boosting, are transforming the real world. These methods…
Manoj S. Kambara, Onyinye Chukka, Kathryn J. Choi, Joseph Tsenum + 4 more
'Sonali Gupta' 'Nolan J. English' 'I. King Jordan' 'Leonardo Mariño-Ramírez'] Type 2 diabetes (T2D) is a disease with high morbidity and mortality and a disproportionate impact on minority groups. Machine learning (ML) is increasingly used to characterize T2D risk factors; however, it has not been used to study T2D…
Andrés Cremades, Sergio Hoyas, Ricardo Vinuesa
For the last 140 years, the mechanisms of transport and dissipation of energy in a turbulent flow have not been completely understood. Previous research has focused on analyzing the so-called coherent structures, organized flow patterns characterized by their spatial coherence, lifespan and significant contribution to…
Shihuan Chen, Xuewei Li, Yan Ouyang, Wei Hong + 6 more
To examine the analytical value of football technical and tactical indicators in post-match outcome analysis, this study used post-match data from 240 matches in the 2024 Chinese Super League (CSL) season and constructed an explainable analytical framework integrating machine learning and SHAP (Shapley Additive…
Yi-Hsin Ko, Chuan-Sheng Hung, Chun-Hung Richard Lin, Yi-Fong Ciou + 6 more
Electrocardiogram (ECG) signals contain important clinical information associated with serum potassium abnormalities. However, in Taiwan, raw patient data and original medical signals generally cannot be taken outside the hospital environment, thereby limiting their subsequent reuse and cross-institutional…
Yugang Cao, Xun Hu, Jun Guo, Tao Fang
Purpose This study aimed to construct and compare machine learning models for predicting recurrent extrahepatic bile duct stones after common bile duct exploration and to clarify the contribution of key risk factors using SHAP analysis, thereby providing a reliable tool for clinical risk assessment and intervention.…
Minami Akao, Yuna Ishikura, Takuma Isshiki, Shinnosuke Tsukada + 4 more
'Hayato Shigetoh' 'Junya Miyazaki' 'Vasiliki Sakellari' 'George Gioftsos'] Objectives: To comprehensively examine the association between spinopelvic alignment and muscle shortening in healthy young men, focusing on the individual and interactive effects of thoracic kyphosis, lumbar lordosis, and anterior pelvic tilt…