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Interpolation estimates values between known data points using polynomial (Lagrange) or spline methods.
Guida passo passo
- 1Input known data points
- 2Choose interpolation type: linear, polynomial, spline
- 3Estimate value at desired point
Esempi risolti
Ingresso
Points: (1,2), (2,4), (3,9)
Risultato
At x=2.5: linear ≈ 6.5, cubic polynomial ≈ 6.5 (both smooth)
Errori comuni da evitare
- ✕Extrapolating beyond data range (unreliable)
- ✕Over-fitting with high-degree polynomials
Domande frequenti
Which interpolation method is best?
Cubic splines usually; balance between fitting and smoothness.
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