![](bga.png)
sembles employing non-linear rules yield more
accurate estimations compared to those utilizing
linear combiners.
• (RQ3): The KNN and MLP combiners appear
to be more suitable for combining estimates pro-
vided by the proposed combinations of single
techniques. Moreover, the SK test demonstrates
that the best cluster in all datasets exclusively
comprises non-linear rules, particularly the KNN
and MLP rules.
Future research directions will explore the use of dif-
ferent single estimators for constructing ensembles
and investigate the effectiveness of other non-linear
rules to develop accurate and stable EEE models.
Additionally, investigating datasets containing mixed
types of features (e.g., numerical and categorical) is
crucial to assess the efficacy of the proposed ensem-
ble methodology.
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