Exploring the potential of incremental feature selection to improve genomic prediction accuracy [PDF]
Genetics Selection Evolution, 2023 Background The ever-increasing availability of high-density genomic markers in the form of single nucleotide polymorphisms (SNPs) enables genomic prediction, i.e.
Felix Heinrich +5 more
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RIFS: a randomly restarted incremental feature selection algorithm. [PDF]
Sci Rep, 2017 AbstractThe advent of big data era has imposed both running time and learning efficiency challenges for the machine learning researchers. Biomedical OMIC research is one of these big data areas and has changed the biomedical research drastically. But the high cost of data production and difficulty in participant recruitment introduce the paradigm of ...
Ye Y, Zhang R, Zheng W, Liu S, Zhou F.
europepmc +4 more sources
A Conditional Mutual Information-Based Approach for Robust Multi-Source Feature Selection in IoT Systems [PDF]
SensorsFeature selection is essential for high-dimensional multi-source feature analysis, particularly in Internet of Things (IoT) environments characterized by data heterogeneity, redundancy, and noise. To address the need to balance classification performance,
Hao Jiang, Shenjie Xu, Yong Shen
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Incremental Feature Selection Oriented for Data with Hierarchical Structure [PDF]
Jisuanji kexue yu tansuo, 2023 In the big data era, the sample size is becoming increasingly large, the data dimensionality is also becoming extremely high, moreover, there exists hierarchical structure between different class labels.
SHE Yanhong, HUANG Wanli, HE Xiaoli, QIAN Ting
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A block matrix incremental feature selection method based on fuzzy rough minimum classification error [PDF]
Scientific ReportsIn fuzzy rough set models, inner-product correlation serves as an effective evaluation function for feature selection, with its key advantage lying in its ability to characterize the minimum classification error inherent in the model.
Zhanwei Chen, Minggang Xing, Juan Li
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An Incremental Approach to Contribution-Based Feature Selection
Journal of Intelligent Systems, 2004 Journal of Intelligent Systems ; 13 ; 1 ; 15-44 ...
Guan, Sheng-Uei, Liu, Jun, Qi, Yinan
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Incremental Perspective for Feature Selection Based on Fuzzy Rough Sets [PDF]
IEEE Transactions on Fuzzy Systems, 2018 Feature selection based on fuzzy rough sets is an effective approach to select a compact feature subset that optimally predicts a given decision label. Despite being studied extensively, most existing methods of fuzzy rough set based feature selection are restricted to computing the whole dataset in batch, which is often costly or even intractable for ...
Xizhao Wang, Degang Chen, Yanyan Yang
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Feature Selection for Modular Networks Based on Incremental Training
Journal of Intelligent Systems, 2005 Journal of Intelligent Systems ; 14 ; 4 ; 353-383 ...
Guan, Sheng-Uei, Liu, Jun
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Incremental unsupervised feature selection for dynamic incomplete multi-view data
Information Fusion, 2023 Multi-view unsupervised feature selection has been proven to be efficient in reducing the dimensionality of multi-view unlabeled data with high dimensions. The previous methods assume all of the views are complete. However, in real applications, the multi-view data are often incomplete, i.e., some views of instances are missing, which will result in ...
Tianrui Li, Xiuwen Yi
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Traffic-Oriented Three-Dimensional Vehicle Reconstruction Using Fixed Roadside Monocular Camera Sensors [PDF]
SensorsFixed roadside monocular cameras are widely used as low-cost sensing devices in intelligent transportation systems; however, extracting reliable three-dimensional (3D) information from such sensors remains challenging due to limited baselines, long ...
Chu Zhang +3 more
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