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Hypergraph Spectra for Unsupervised Feature Selection [PDF]
, 2012 Most existing feature selection methods focus on ranking individual features based on a utility criterion, and select the optimal feature set in a greedy manner. However, the feature combinations found in this way do not give optimal classification performance, since they neglect the correlations among features.
Zhihong Zhang 0001, Edwin R. Hancock
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Cluster Density Properties Define a Graph for Effective Pattern Feature Selection
IEEE Access, 2020 Feature selection is a challenging problem that occurs in the high-dimensional data analysis of many major applications. It addresses the curse of dimensionality by determining a small set of features to represent high-dimensional data without ...
Khadidja Henni +2 more
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BMC Medical Genomics, 2022 Background Feature selection of multi-omics data analysis remains challenging owing to the size of omics datasets, comprising approximately $$10^2$$ 10 2 – $$10^5$$ 10 5 features. In particular, appropriate methods to weight individual omics datasets are
Y-h. Taguchi, Turki Turki
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Unsupervised Feature Selection by Pareto Optimization
Proceedings of the AAAI Conference on Artificial Intelligence, 2019 Dimensionality reduction is often employed to deal with the data with a huge number of features, which can be generally divided into two categories: feature transformation and feature selection. Due to the interpretability, the efficiency during inference and the abundance of unlabeled data, unsupervised feature selection has attracted much attention ...
Chao Feng 0006 +2 more
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Unsupervised Feature Selection and Clustering Optimization Based on Improved Differential Evolution
IEEE Access, 2019 The feature selection method based on supervised learning has been widely studied and applied to the field of machine learning and data mining. But unsupervised feature selection is still a tricky area of research because the unavailability of the label ...
Tao Li, Hongbin Dong
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Molecular Oncology, EarlyView.In this explorative study, the abundance of circular RNA molecules in bone marrow stem cells was found to be elevated in patients with high‐risk myelodysplastic neoplasms, and to be associated with an increased risk of progression to acute myeloid leukemia.
Eileen Wedge +17 more
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Molecular Oncology, EarlyView.RNA profiling of circulating extracellular vesicles (EVs) from blood samples of men undergoing prostate biopsy identifies transcripts associated with clinically significant prostate cancer. Integrative analysis with public tumor datasets links EV‐derived gene signatures to tumor stage and progression‐free survival, highlighting CASP3, XRCC2, and RIT1 ...
Stefan Werner +14 more
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Molecular Oncology, EarlyView.This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingBand selection is a critical step in processing hyperspectral imagery (HSI); reducing input dimensionality allows models to mitigate redundancy, enhance computational efficiency, and improve learning accuracy.
Jacqueline Liu +2 more
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IEEE Access, 2020 Non-small-cell lung cancer (NSCLC) is the most common type of lung cancer, which accounts for a proportion of nearly 85%. The increasing availability of genome-wide gene expression data has facilitated the identification of gene signatures that are ...
Xiucai Ye +2 more
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