 Study  Ensemble type  Base learner(s)  Combination rule(s)  Number of datasets 

Braga et al. [22]  Homogeneous (bagging)  Linear regression  Linear (averaging) 
1  Homogeneous (bagging)  MLP  Linear (averaging)  Homogeneous (bagging)  M5P regression trees  Linear (averaging)  Homogeneous (bagging)  M5P model trees  Linear (averaging)  Homogeneous (bagging)  SVR  Linear (averaging) 
 Kultur et al. [23, 24]  Homogeneous (bootstrapping)  MLP  Nonlinear (average of largest cluster obtained using adaptive resonance theory (ART) algorithm)  5 

Minku and Yao [25, 26]  Homogeneous (bagging, random, negative correlation learning)  MLP  Linear (averaging) 
18  Homogeneous (bagging)  RBF  Linear (averaging)  Homogeneous (bagging)  Regression Trees  Linear (averaging) 
 Kocaguneli et al. [27]  Heterogeneous  Gaussian process, MLP, RBF, SMOReg, SVMReg, IBk, LWL, additive regression, bagging with decision tree, RandomSubSpace, DecisionStump, M5P, ConjunctiveRule, DecisionTable  Linear (averaging)  3 
 Kocaguneli et al. [28]  Heterogeneous  ABE01NN, ABE05NN, SWReg, CART (yes), CART (no), NNet, LReg, PCR, PLSR  Linear (mean, median, inverseranked weighted mean (IRWM))  20 
 Elish [29]  Heterogeneous  MLP, RBF, RT, KNN, SVR  Linear (median)  5 
  Homogeneous (bagging)  MLP  Linear (averaging, weighted averaging) and nonlinear (MLP SVR, FISFCM, FISSC, ANFISFCM, ANFISSC)   This paper  Homogeneous (bagging)  SVR 
5  Homogeneous (bagging)  ANFIS   Heterogeneous  MLP, SVR, ANFIS  

