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Factored Scoring is a method of evaluation that assigns weights to multiple criteria, then calculates a composite score to rank options. In Orion AI, factored scoring might weigh fundamentals, technical indicators, and sentiment to produce a final stock rating. In Freddie AI, it could combine skills, experience, test results, and cultural fit to rank candidates. Factored scoring improves decision-making by ensuring that no single criterion dominates the evaluation process. It also enables customization for different industries or use cases, making it adaptable to various decision contexts. AI enhances factored scoring by processing large datasets and continually refining the weighting model based on historical performance.
