Several models can agree because they share the same blind spot. A combined prediction therefore needs evaluation rather than confidence based on the number of models involved.
Scikit-learn describes ensemble methods that combine predictions from multiple estimators. Scikit-learn — ensemble.
Inspect shared failures
For a photo task, compare whether the component models all struggle with the same background or product family. Apparent diversity in model names does not establish diversity in errors.
Include operating costs
Review latency, maintenance and reproducibility alongside predictive results. A more complicated combination may create additional dependencies without a useful improvement. Keep the combination rule and evaluation conditions explicit so a later component replacement can be assessed meaningfully.
Source reviewed 25 October 2026. Interpretation and original diagrams: PLUSHIP / Qunhe. Examples are illustrative.
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