fitting
What It Means
Fitting is the process of checking whether data values fall within acceptable ranges or boundaries that were defined beforehand. It's essentially a validation step that confirms your data meets predetermined criteria or standards before it gets used in AI systems or business processes.
Why Chief AI Officers Care
Poor fitting can lead to AI models trained on invalid data, resulting in unreliable predictions and flawed business decisions. It's also critical for regulatory compliance, as many industries require proof that data used in AI systems meets specific quality standards and operational parameters.
Real-World Example
A financial services company sets acceptable credit score ranges of 300-850 for their loan approval AI system. The fitting process would flag and reject any credit score data points outside this range, such as negative numbers or scores above 850, before they contaminate the model's training data.
Common Confusion
People often confuse fitting with model fitting or curve fitting in machine learning, but this definition refers specifically to data validation against predefined boundaries, not the process of training algorithms to match patterns in data.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare AI, fitting involves validating that patient data conforms to clinical standards and regulatory requiremen...
Finance: In finance, fitting refers to validating that financial data, models, and AI outputs conform to regulatory requirements ...
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Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"Fitting is the process of verifying whether the data item value is in the previously specified interval."Source: OECD
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