Table 5 Shows the different measured matrices of stage 2 with cross validation of 10k.

From: Machine learning enhanced ultra-high vacuum system for predicting field emission performance in graphene reinforced aluminium based metal matrix composites

Model

MSE

RMSE

R2

Adj R2

Stacking

105.8359

10.28766

0.936577

0.934312

CatBoost_GPR

113.7563

10.66566

0.924768

0.922081

XGBoost_GPR

118.7712

10.89822

0.91918

0.916294

CatBoost_SVR

124.0534

11.13792

0.905925

0.902565

LightGBM_GPR

122.3743

11.06229

0.905845

0.902482

XGBoost_SVR

129.603

11.38433

0.895379

0.891643

CatBoost_Polynomial

152.4879

12.3486

0.890368

0.886453

LightGBM_SVR

132.7601

11.52216

0.888728

0.884754

CatBoost_RF

139.3082

11.80289

0.886352

0.882293

XGBoost_RF

145.4651

12.06089

0.885757

0.881676

Voting

134.1475

11.5822

0.880764

0.876506

XGBoost_Polynomial

156.7894

12.52156

0.876171

0.871749

LightGBM_RF

149.0294

12.20776

0.876072

0.871646

Bagging_RF

166.5806

12.90661

0.859916

0.854913

LightGBM_Polynomial

160.6914

12.67641

0.85754

0.852452

Bagging_SVR

148.864

12.20099

0.838697

0.832936

Bagging_GPR

136.8502

11.6983

0.838505

0.832737

Bagging_Polynomial

179.2294

13.38766

0.829093

0.822989

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