Results 11 to 20 of about 1,793,798 (289)
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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Hierarchical feature selection for ranking [PDF]
Proceedings of the 19th international conference on World wide web, 2010 Ranking is an essential part of information retrieval(IR) tasks such as Web search. Nowadays there are hundreds of features for ranking. So learning to rank(LTR), an interdisciplinary field of IR and machine learning(ML), has attracted increasing attention.
Guichun Hua +4 more
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Linear feature extraction for ranking [PDF]
Information Retrieval Journal, 2018 We address the feature extraction problem for document ranking in information retrieval. We then propose LifeRank, a Linear feature extraction algorithm for Ranking. In LifeRank, we regard each document collection for ranking as a matrix, referred to as the original matrix.
Gaurav Pandey 0003 +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 ...
Prati, Ronaldo C., Ronaldo C. Prati
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CoRR, 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 ...
Bitya Neuhof, Yuval Benjamini
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Computers, 2023 Feature selection is a crucial step in machine learning, aiming to identify the most relevant features in high-dimensional data in order to reduce the computational complexity of model development and improve generalization performance.
László Göcs, Zsolt Csaba Johanyák
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An incremental approach to MSE-based feature selection [PDF]
, 2007 Feature selection plays an important role in classification systems. Using classifier error rate as the evaluation function, feature selection is integrated with incremental training.
Guan, SU, Bao, C, Qi, Y
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Information, 2022 Globally, smart cities, infrastructure, and transportation have led to a rise in vehicle numbers, resulting in an increasing number of problems. This includes problems such as air pollution, noise pollution, high energy consumption, and people’s health ...
Manish Kumar Pandey +4 more
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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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Relational Regularization and Feature Ranking [PDF]
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014 Regularization is one of the key concepts in machine learning, but so far it has received only little attention in the logical and relational learning setting. Here we propose a regularization and feature selection technique for such setting, in which one commonly represents the structure of the domain using an entity-relationship model.
Fabrizio Costa +2 more
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