Approximation error
Approximation error is the discrepancy between an exact or target quantity and an approximate representation, estimate, computation, or model.
Advanced Algorithms and Data Structures
Approximation error is a nonnegative factor that bounds how far an approximate nearest-neighbor result may be from the corresponding exact result.
- How it is used
- Controls early termination in approximate nearest-neighbor search by trading search effort for a bounded distance error.
- How deep it goes
- Defines the distance guarantee and derives the pruning threshold, but does not provide a formal proof.
- Examples
- Uses query points P and Z, candidates Q and N, pruning bounds, and a traversal with ϵ approximately 0.25.
- What you can do after
- Apply it via branch-pruning rules that guarantee an approximate nearest-neighbor distance within a factor of the exact result.
Read how Advanced Algorithms and Data Structures explains approximation error →
Experimentation for Engineers
The difference between a model's estimated response and the measured response it approximates.
- How it is used
- Uses approximation error to assess a surrogate function that interpolates measured profit while optimizing a continuous threshold.
- How deep it goes
- Defines the error algebraically and distinguishes exact interpolation from typical nonzero error, then implements the fitted surrogate.
- Examples
- Uses aggregate profit measurements, a quadratic threshold model, matrix normal equations, and NumPy interpolation code.
- What you can do after
- Evaluate surrogate-versus-measurement differences and interpolate predicted responses with NumPy.
Read how Experimentation for Engineers explains approximation error →
Related concepts
- quantizationproduced by · Quantization maps numerical values to a finite set of discrete representations, often using reduced precision to lower model storage or computation requirements.
- pruning criterionused by · A pruning criterion is a rule that compares a branch's possible distance with the current nearest-neighbor distance to decide whether to skip the branch.
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