Linear Basis Function Models

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Linear Basis Function Models

  • polynomial functions: changes in one region affect all other regions.
    • spline functions : don't have to worry about globalness.
  • Gaussian functions : \(\exp\{-\frac{(x-\mu)^2}{2s^2}\}\)
  • sigmoidal functions : \(\sigma(\frac{x-\mu}{s})\), while \(\sigma(a)\) is the logistic sigmoid function defined by \(\sigma(a) = \frac{1}{1 + \exp(-a)}\).
    • tanh functions : \(\tanh(a) = 2\sigma(a) - 1\).
  • Fourier basis : an expansion in sinusoidal functions.
    • wavelets

Reference

  • Pattern Recognition and Machine Learning, Christopher M. Bishop

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