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Journal of Big Data

Table 7 BERTweet stacking ensemble (SE) result

From: A BERTweet-based design for monitoring behaviour change based on five doors theory on coral bleaching campaign

Scenario Description Accuracy F1 score
SE#1 modelSE#1 0.7429 0.6786
SE#2 modelSE#2 0.7592 0.7399
SE#3 modelSE#3 0.7673 0.7473
SE#4 modelSE#4 0.7429 0.7436
SE#5 combination1 (modelSE#1 and modelSE#2) 0.7755 0.7677
SE#6 combination2 (modelSE#1 and modelSE#3) 0.7551 0.7530
SE#7 combination3 (modelSE#1 and modelSE#4) 0.7551 0.7298
SE#8 combination4 (modelSE#2 and modelSE#3) 0.7388 0.7236
SE#9 combination5 (modelSE#2 and modelSE#4) 0.7633 0.7829
SE#10 combination6 (modelSE#3 and modelSE#4) 0.7592 0.7754
SE#11 combinationAll (modelSE#1—modelSE#4) 0.7796 0.7945
  1. Scenario SE#3 is bolded because it has the best performance out of all standalone models, scenario SE#9 is bolded because it has the best performance out of the combination of two models and SE#11 is bolded because it has the best performance out of the combination of four models
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