Suchergebnisse - algorithm explainability

S-SIRUS: an explainability algorithm for spatial regression Random Forest: S-SIRUS: an explainability algorithm von Patelli, Luca, Golini, Natalia, Ignaccolo, Rosaria, Cameletti, Michela

“… Random Forest (RF) is a widely used machine learning algorithm known for its flexibility, user-friendliness, and high predictive performance across various domains …”
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Parallel approaches for a decision tree-based explainability algorithm von Loreti, Daniela, Visani, Giorgio

“… The explainability research field is precisely devoted to investigating techniques able to give an interpretation of ML algorithms’ predictions …”
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S-SIRUS: an explainability algorithm for spatial regression Random Forest von Patelli, Luca, Golini, Natalia, Ignaccolo, Rosaria, Cameletti, Michela

“… Random Forest (RF) is a widely used machine learning algorithm known for its flexibility, user-friendliness, and high predictive performance across various domains …”
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Clinical Explainability Failure (CEF) & Explainability Failure Ratio (EFR) – Changing the Way We Validate Classification Algorithms von Venugopal, Vasantha Kumar, Takhar, Rohit, Gupta, Salil, Mahajan, Vidur

“… Adoption of Artificial Intelligence (AI) algorithms into the clinical realm will depend on their inherent trustworthiness, which is built not only by robust validation studies but is also deeply linked to the explainability …”
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Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation von Ng, Ada, Wei, Boyang, Jain, Jayalakshmi, Ward, Erin A, Tandon, S Darius, Moskowitz, Judith T, Krogh-Jespersen, Sheila, Wakschlag, Lauren S, Alshurafa, Nabil

“… Background: Cognitive behavioral therapy–based interventions are effective in reducing prenatal stress, which can have severe adverse health effects on mothers …”
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Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability von Herm, Lukas-Valentin, Heinrich, Kai, Wanner, Jonas, Janiesch, Christian

“… Machine learning models with higher performance are often based on more complex algorithms and therefore lack explainability and vice versa …”
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Evaluation of Machine Learning Algorithms and Explainability Techniques to Detect Hearing Loss From a Speech-in-Noise Screening Test von Lenatti, Marta, Moreno-Sánchez, Pedro A, Polo, Edoardo M, Mollura, Maximiliano, Barbieri, Riccardo, Paglialonga, Alessia

“… ) models applied to a speech-in-noise hearing screening test and investigate the contribution of the measured features toward hearing loss detection using explainability …”
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An algorithm to optimize explainability using feature ensembles von Lazebnik, Teddy, Bunimovich-Mendrazitsky, Svetlana, Rosenfeld, Avi

“… However, current feature ensemble algorithms do not consider explainability as a key factor in their construction …”
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Enhanced Model for Gestational Diabetes Mellitus Prediction Using a Fusion Technique of Multiple Algorithms with Explainability von Hassan, Ahmad, Ahmad, Saima Gulzar, Iqbal, Tassawar, Munir, Ehsan Ullah, Ayyub, Kashif, Ramzan, Naeem

“… It uses conventional Machine Learning (ML) and advanced Deep Learning (DL) algorithms. Subsequently, it combines the strengths of both ML and DL algorithms using various ensemble techniques …”
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Imbalanced rock burst assessment using variational autoencoder-enhanced gradient boosting algorithms and explainability von Lin, Shan, Liang, Zenglong, Dong, Miao, Guo, Hongwei, Zheng, Hong

“… We conducted a study to evaluate the potential and robustness of gradient boosting algorithms in rock burst assessment, established a variational autoencoder (VAE …”
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Explainability-based Trust Algorithm for electricity price forecasting models von Heistrene, Leena, Machlev, Ram, Perl, Michael, Belikov, Juri, Baimel, Dmitry, Levy, Kfir, Mannor, Shie, Levron, Yoash

“… Advanced machine learning (ML) algorithms have outperformed traditional approaches in various forecasting applications, especially electricity price forecasting (EPF …”
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STD-Explain: Generalizing explanations for spatio-temporal graph convolutional networks based on spatio-temporal decoupled perturbation von Li, Yanshan, Shi, Ting, He, Suixuan, Chen, Zhiyuan, Zhang, Li, Yu, Rui, Xie, Weixin

“… of spatio-temporal data, posing challenges for existing explainability algorithms to effectively separate and interpret these intertwined features …”
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Deep Neural Networks Explainability: Algorithms and Applications von Du, Mengnan

“… Consider, for instance, an advanced self-driving car equipped with various DNN algorithms doesn't brake or decelerate when confronting a stopped firetruck …”
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Kurz erklärt: Measuring Data Changes in Data Engineering and their Impact on Explainability and Algorithm Fairness von Klettke, Meike, Lutsch, Adrian, Störl, Uta

“… In machine learning processes requirements such as fairness and explainability are essential …”
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Decoding student cognitive abilities: a comparative study of explainable AI algorithms in educational data mining von Niu, Tianyue, Liu, Ting, Luo, Yiming Taclis, Pang, Patrick Cheong-Iao, Huang, Shuaishuai, Xiang, Ao

“… This study employs data-driven artificial intelligence (AI) models supported by explainability algorithms and PSM causal inference to investigate the factors influencing students …”
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Explainability: Relevance based dynamic deep learning algorithm for fault detection and diagnosis in chemical processes von Agarwal, Piyush, Tamer, Melih, Budman, Hector

“… •An Explainability based methodology is employed for deriving contribution plots for fault diagnosis …”
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Predicting financial crises: an evaluation of machine learning algorithms and model explainability for early warning systems von Reimann, Chris

“… This paper addresses the critical challenge of detecting financial crises in their early stages given their profound economic and societal consequences. It …”
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Explainability in RIONA Algorithm Combining Rule Induction and Instance-Based Learning von Gora, Grzegorz, Skowron, Andrzej, Wojna, Arkadiusz

“… The article concerns the well-known RIONA algorithm. We focus on the explainability property of this algorithm …”
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Risk Stratification for Herpes Simplex Virus Pneumonia Using Elastic Net Penalized Cox Proportional Hazard Algorithm with Enhanced Explainability von Wang, Yu-Chiang, Lin, Wan-Ying, Tseng, Yi-Ju, Fu, Yiwen, Li, Weijia, Huang, Yu-Chen, Wang, Hsin-Yao

“… In this study, we developed and validated a risk stratification model for HSV bronchopneumonia using an elastic net penalized Cox proportional hazard algorithm …”
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Explainability in deep reinforcement learning von Heuillet, Alexandre, Couthouis, Fabien, Díaz-Rodríguez, Natalia

“… ), a relatively new subfield of Explainable Artificial Intelligence, intended to be used in general public applications, with diverse audiences, requiring ethical, responsible and trustable algorithms …”
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