Results 11 to 20 of about 7,127,658 (298)
Quantifying feature importance for online content moderation [PDF]
EPJ Data ScienceAccurately estimating how users respond to moderation interventions is key to designing effective and user-centred moderation strategies. This requires understanding which user characteristics are associated with different behavioural responses.
Benedetta Tessa +4 more
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Sparseness-Optimized Feature Importance [PDF]
In this paper, we propose a model-agnostic post-hoc explanation procedure devoted to computing feature attribution. The proposed method, termed Sparseness-Optimized Feature Importance (SOFI), entails solving an optimization problem related to the sparseness of feature importance explanations.
Grau, Isel, Nápoles, Gonzalo
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Permutation importance: a corrected feature importance measure [PDF]
Bioinformatics, 2010 Abstract Motivation: In life sciences, interpretability of machine learning models is as important as their prediction accuracy. Linear models are probably the most frequently used methods for assessing feature relevance, despite their relative inflexibility.
André Altmann +3 more
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Information, 2023 Diabetes is a chronic disease caused by a persistently high blood sugar level, causing other chronic diseases, including cardiovascular, kidney, eye, and nerve damage.
Md. Jamal Uddin +8 more
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Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2022 Predicting early Type 2 diabetes (T2D) is critical for improved care and better T2D outcomes. An accurate and efficient T2D prediction relies on unbiased relevant features.
Mila Desi Anasanti +2 more
doaj +1 more source
Local Explanations of Global Rankings: Insights for Competitive Rankings
IEEE Access, 2022 Explaining complex algorithms and models has recently received growing attention in various domains to support informed decisions. Ranking functions are widely used for almost every form of human activity to enable effective decision-making processes ...
Hadis Anahideh +1 more
doaj +1 more source
Logic Constraints to Feature Importance
, 2022 In recent years, Artificial Intelligence (AI) algorithms have been proven to outperform traditional statistical methods in terms of predictivity, especially when a large amount of data was available. Nevertheless, the "black box" nature of AI models is often a limit for a reliable application in high-stakes fields like diagnostic techniques, autonomous
Nicola Picchiotti, Marco Gori
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Big Data and Cognitive Computing, 2023 This paper investigated the importance of explainability in artificial intelligence models and its application in the context of prediction in Formula (1).
William Villegas-Ch +2 more
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Sakarya University Journal of Computer and Information Sciences, 2020 The whole world has been fighting against the novel coronavirus 2019 (COVID-19) for months. Despite the advances in medical sciences, more than 235,000 people have died so far.
Abdullah Talha Kabakuş
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Feature importance calculated by feature engineering.
, 2023 Feature importance calculated by feature engineering.
Qazi Arbab Ahmed (17200020) +10 more
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