Polynomial Function Fitting Task

A Polynomial Function Fitting Task is a non-linear function fitting task that requires the production of a (best-fitting) fitted polynomial function.

• AKA: Linear Regression.
• Context:
  • Input: a Numerically-Labeled Training Dataset.
  • output: a Fitted Polynomial Function.
  • It can be solved by a Polynomial Regression System (that implements a polynomial regression algorithm).
• Example(s):
  • …
• Counter-Example(s):
  • Exponential Function Fitting.
  • Analysis of Variance.
  • Supervised Classification.
• See: System of Polynomial Equations, Polynomial Program.

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References

2013

• http://mathworld.wolfram.com/LeastSquaresFittingPolynomial.html
  • QUOTE: Generalizing from a straight line (i.e., first degree polynomial) to a kth degree polynomial :[math]\displaystyle{ y=a_0+a_1x+...+a_kx^k, (1) }[/math] the residual is given by [math]\displaystyle{ R^2=sum_(i=1)^n[y_i-(a_0+a_1x_i+...+a_kx_i^k)]^2 }[/math].

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