Results 11 to 20 of about 88,907 (241)
, 2023 Machine learning models are widely applied in various fields. Stakeholders often use post-hoc feature importance methods to better understand the input features' contribution to the models' predictions. The interpretation of the importance values provided by these methods is frequently based on the relative order of the features (their ranking) rather ...
Neuhof, Bitya, Benjamini, Yuval
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Frontiers in Veterinary Science, 2023 IntroductionMyxomatous mitral valve disease (MMVD) is the most common cause of heart failure in dogs, and assessing the risk of heart failure in dogs with MMVD is often challenging.
Yunji Kim +5 more
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Computers, 2021 The aim of this research study is to detect emotional state by processing electroencephalography (EEG) signals and test effect of meditation music therapy to stabilize mental state.
Nisha Vishnupant Kimmatkar +1 more
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Feature ranking for semi-supervised learning
Machine Learning, 2022 AbstractThe data used for analysis are becoming increasingly complex along several directions: high dimensionality, number of examples and availability of labels for the examples. This poses a variety of challenges for the existing machine learning methods, related to analyzing datasets with a large number of examples that are described in a high ...
Matej Petković +2 more
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Ensemble Feature Ranking [PDF]
, 2004 A crucial issue for Machine Learning and Data Mining is Feature Selection, selecting the relevant features in order to focus the learning search. A relaxed setting for Feature Selection is known as Feature Ranking, ranking the features with respect to their relevance.
Jong, Kees +4 more
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Ensemble feature selection approach based on feature ranking for rice seed images classification
Advances in Electrical and Electronic Engineering, 2020 In smart agriculture, rice variety inspection systems based on computer vision need to be used for recognizing rice seeds instead of using technical experts.
Dzi Lam Tran Tuan +3 more
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Reconstructing dynamical networks via feature ranking [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2019 Empirical data on real complex systems are becoming increasingly available. Parallel to this is the need for new methods of reconstructing (inferring) the structure of networks from time-resolved observations of their node-dynamics. The methods based on physical insights often rely on strong assumptions about the properties and dynamics of the ...
Marc G. Leguia +3 more
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Family Rank: a graphical domain knowledge informed feature ranking algorithm
Bioinformatics, 2021 Abstract Motivation When designing prediction models built with many features and relatively small sample sizes, feature selection methods often overfit training data, leading to selection of irrelevant features.
Michelle Saul, Valentin Dinu
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Deep Feature Ranking for Person Re-Identification
IEEE Access, 2019 Person re-identification plays a critical part in many surveillance applications. Due to complicated illumination environments and various viewpoints, it is still a challenging problem to extract robust features.
Jie Nie +4 more
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AutoEncoder-based feature ranking for Alzheimer Disease classification using PET image
Machine Learning with Applications, 2021 This paper presents a method of ranking the effectiveness of brain region of interest (ROI) in order to separate Normal Control (NC) from Alzheimer’s disease (AD) brains Positron Emission Tomography (PET) images based on AutoEncoder (AE) networks ...
Pham Minh Tuan +4 more
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