Results 21 to 30 of about 88,907 (241)
Energies, 2021 This work proposes a data-driven methodology for identifying critical components in Complex Technical Infrastructures (CTIs), for which the functional logic and/or the system structure functions are not known due the CTI’s complexity and evolving nature.
Ahmed Shokry +4 more
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Combining feature ranking algorithms through rank aggregation [PDF]
The 2012 International Joint Conference on Neural Networks (IJCNN), 2012 The problem of combining multiple feature rankings into a more robust ranking is investigated. A general framework for ensemble feature ranking is proposed, alongside four instantiations of this framework using different ranking aggregation methods. An empirical evaluation using 39 UCI datasets, three different learning algorithms and three different ...
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Feature Ranking for Total Ordering Ranking Problems
Proceedings of the 2010 International Conference on E-Business Intelligence, 2010 In this paper, we first introduce the development of learning to rank and discuss the problems existing in this field especially the ignorance of total ordering ranking. For dealing with the total ordering ranking problem, we assume a method “feature ranking”. Based the assumption, we design two algorithms: Feature Rank and BL-FeatureRank.
Daniel Zeng, Yongqing Wang
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Fast Feature Ranking Algorithm [PDF]
, 2003 The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simpler and easy to understand. The algorithm has some interesting characteristics: lower computational cost (O(m n log n) m attributes and n examples in the data set) with respect ...
Ruiz Sánchez, Roberto +2 more
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Classification with correlated features: unreliability of feature ranking and solutions [PDF]
Bioinformatics, 2011 AbstractMotivation: Classification and feature selection of genomics or transcriptomics data is often hampered by the large number of features as compared with the small number of samples available. Moreover, features represented by probes that either have similar molecular functions (gene expression analysis) or genomic locations (DNA copy number ...
Tolosi, L., Lengauer, T.
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Number of Instances for Reliable Feature Ranking in a Given Problem
Business Systems Research, 2018 Background: In practical use of machine learning models, users may add new features to an existing classification model, reflecting their (changed) empirical understanding of a field. New features potentially increase classification accuracy of the model
Bohanec Marko +2 more
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Mathematics, 2023 In this paper, we propose and compare new methodologies for ranking the importance of variables in productive processes via an adaptation of OneClass Support Vector Machines.
Raul Moragues +2 more
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Insights into distributed feature ranking [PDF]
Information Sciences, 2019 Xunta de Galicia; ED431G ...
Verónica Bolón-Canedo +4 more
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Predicting Diabetes Mellitus With Machine Learning Techniques
Frontiers in Genetics, 2018 Diabetes mellitus is a chronic disease characterized by hyperglycemia. It may cause many complications. According to the growing morbidity in recent years, in 2040, the world’s diabetic patients will reach 642 million, which means that one of the ten ...
Quan Zou +6 more
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Parameter Averaging for Feature Ranking
, 2022 Neural Networks are known to be sensitive to initialisation. The methods that rely on neural networks for feature ranking are not robust since they can have variations in their ranking when the model is initialized and trained with different random seeds.
Ucar, Talip, Hajiramezanali, Ehsan
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