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Table 1 22 ensemble learning methods concerned with the detection of breast cancer

From: EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer

  Method name Publication year
1 Bayesian networks-based model integration [14, 15] 2006 and 2019
2 RSS-SCS method [16] 2016
3 Collective approach (correlation, color palette, color proportion, and SVM) [17] 2016
4 Kernel-based Data Fusion Method for Gene Prioritization [18] 2015
5 DECORATE methoda [19] 2015
6 HyDRA methoda [20] 2015
7 GenEnsemble methoda (NBS-IB3-SVM-C4.5 DT) [21] 2014
8 NB (Naïve Bayes) combiner method [22] 2014
9 Evolutionary Ensemble Model [23] 2014
10 smoothed t-statistic SVM (stSVM) [24] 2013
11 SVM Classifiers Fusion (three SVM) [25] 2013
12 COMBINER (Core Module Biomarker Identification)a [26] 2012
13 Ensembles of BioHEL Rule Set [27] 2012
14 Stacking IB3-NBS-RF-SVM method [28] 2012
15 REIS-based ensemble method [29] 2011
16 MRS method [30] 2010
17 Boosting-TWSVM method [31] 2009
18 Bagging and boosting-based TWSVM [32] 2009
19 Feature Subsets Method [33] 2008
20 BNCE method [34] 2007
21 Bayesian Network Classifier [35] 2006
22 enSVM (200 SVM) [36] 2006
  1. aSome methods that are proposed to discover genomic markers related to breast cancer