These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
1006 related articles for article (PubMed ID: 26674595)
1. The feature selection bias problem in relation to high-dimensional gene data. Krawczuk J; Ćukaszuk T Artif Intell Med; 2016 Jan; 66():63-71. PubMed ID: 26674595 [TBL] [Abstract][Full Text] [Related]
2. Ensemble Feature Learning of Genomic Data Using Support Vector Machine. Anaissi A; Goyal M; Catchpoole DR; Braytee A; Kennedy PJ PLoS One; 2016; 11(6):e0157330. PubMed ID: 27304923 [TBL] [Abstract][Full Text] [Related]
3. A fast gene selection method for multi-cancer classification using multiple support vector data description. Cao J; Zhang L; Wang B; Li F; Yang J J Biomed Inform; 2015 Feb; 53():381-9. PubMed ID: 25549938 [TBL] [Abstract][Full Text] [Related]
4. Feature selection and nearest centroid classification for protein mass spectrometry. Levner I BMC Bioinformatics; 2005 Mar; 6():68. PubMed ID: 15788095 [TBL] [Abstract][Full Text] [Related]
6. Recursive Mahalanobis separability measure for gene subset selection. Mao KZ; Tang W IEEE/ACM Trans Comput Biol Bioinform; 2011; 8(1):266-72. PubMed ID: 20479500 [TBL] [Abstract][Full Text] [Related]
7. A novel random forests-based feature selection method for microarray expression data analysis. Yao D; Yang J; Zhan X; Zhan X; Xie Z Int J Data Min Bioinform; 2015; 13(1):84-101. PubMed ID: 26529910 [TBL] [Abstract][Full Text] [Related]
8. A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue. Chen Z; Li J; Wei L Artif Intell Med; 2007 Oct; 41(2):161-75. PubMed ID: 17851055 [TBL] [Abstract][Full Text] [Related]
9. Gene and sample selection using T-score with sample selection. Mundra PA; Rajapakse JC J Biomed Inform; 2016 Feb; 59():31-41. PubMed ID: 26556644 [TBL] [Abstract][Full Text] [Related]
10. Stable gene selection from microarray data via sample weighting. Yu L; Han Y; Berens ME IEEE/ACM Trans Comput Biol Bioinform; 2012; 9(1):262-72. PubMed ID: 21383420 [TBL] [Abstract][Full Text] [Related]
11. C-HMOSHSSA: Gene selection for cancer classification using multi-objective meta-heuristic and machine learning methods. Sharma A; Rani R Comput Methods Programs Biomed; 2019 Sep; 178():219-235. PubMed ID: 31416551 [TBL] [Abstract][Full Text] [Related]
12. Mixture classification model based on clinical markers for breast cancer prognosis. Zeng T; Liu J Artif Intell Med; 2010; 48(2-3):129-37. PubMed ID: 20005686 [TBL] [Abstract][Full Text] [Related]
13. Robust feature selection for microarray data based on multicriterion fusion. Yang F; Mao KZ IEEE/ACM Trans Comput Biol Bioinform; 2011; 8(4):1080-92. PubMed ID: 21566255 [TBL] [Abstract][Full Text] [Related]
14. Supervised, Unsupervised, and Semi-Supervised Feature Selection: A Review on Gene Selection. Ang JC; Mirzal A; Haron H; Hamed HN IEEE/ACM Trans Comput Biol Bioinform; 2016; 13(5):971-989. PubMed ID: 26390495 [TBL] [Abstract][Full Text] [Related]
15. Feature selection and tumor classification for microarray data using relaxed Lasso and generalized multi-class support vector machine. Kang C; Huo Y; Xin L; Tian B; Yu B J Theor Biol; 2019 Feb; 463():77-91. PubMed ID: 30537483 [TBL] [Abstract][Full Text] [Related]
16. An efficient statistical feature selection approach for classification of gene expression data. Chandra B; Gupta M J Biomed Inform; 2011 Aug; 44(4):529-35. PubMed ID: 21241823 [TBL] [Abstract][Full Text] [Related]
17. Recursive feature selection with significant variables of support vectors. Tsai CA; Huang CH; Chang CW; Chen CH Comput Math Methods Med; 2012; 2012():712542. PubMed ID: 22927888 [TBL] [Abstract][Full Text] [Related]
18. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine. Xi M; Sun J; Liu L; Fan F; Wu X Comput Math Methods Med; 2016; 2016():3572705. PubMed ID: 27642363 [TBL] [Abstract][Full Text] [Related]
19. Identification of potential biomarkers on microarray data using distributed gene selection approach. Shukla AK; Tripathi D Math Biosci; 2019 Sep; 315():108230. PubMed ID: 31326384 [TBL] [Abstract][Full Text] [Related]
20. Exploring correlations in gene expression microarray data for maximum predictive-minimum redundancy biomarker selection and classification. Arevalillo JM; Navarro H Comput Biol Med; 2013 Oct; 43(10):1437-43. PubMed ID: 24034735 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]