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Fig. 1 | BMC Research Notes

Fig. 1

From: A greedy stacking algorithm for model ensembling and domain weighting

Fig. 1

Schematic overview of both example cases for the greedy weighting algorithm. Numbers in the plots are just for illustration. a Logistic regression, Random Forest, and naive Bayes learners are combined to achieve a more accurate ensemble learner for classification. For regression tasks, Random Forest, linear regression, and support vector regression was used. b The GIMD is a weighted combination of different domains of deprivation

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