Estimating from No Data: Deriving a Continuous Score from Categories

# Estimating from No Data: Deriving a Continuous Score from Categories Researchers have figured out how to get detailed, precise ratings from AI systems even when they're only trained on simple yes/no or category-based feedback. This means companies can build scoring systems (like customer satisfaction ratings or product quality rankings) without needing extensive manual labeling of every possible score level. It's a practical shortcut for situations where detailed training data is hard to come by.
A walkthrough of and the maths behind using low-capacity networks to acquire fine-grained scoring when only categorical labelling is available for training The post Estimating from No Data: Deriving a Continuous Score from Categories appeared first on Towards Data Science.
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