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Approximation error

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TL;DR. The difference or discrepancy between an exact value and its approximated value.

Technical Definition

The difference or discrepancy between an exact value and its approximated value.

How it works

Approximation error is the quantifiable difference between a precise value and its approximation. This error arises when a value is rounded, truncated, or otherwise simplified, and is a fundamental concept in numerical analysis and computation.

Further Reading

  • Wikipedia — Glossary of AI