Figure 1
A diagram depicts an ensemble learning process where an Input feeds multiple Learners whose outputs combine in an Ensemble model to produce an Output.The diagram illustrates an ensemble learning architecture in which an Input is provided simultaneously to Learner 1, Learner 2, and Learner m. Each Learner processes the Input independently and sends its result forward through weighted connections labelled g 1, g 2, and g m. These weighted outputs converge into a single Ensemble model block, which aggregates the individual Learner contributions. The Ensemble model then generates a final Output, showing how multiple models are combined to improve overall predictive performance.

Fundamentals of ensemble model

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