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Implementation
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Numerical Methods | |
Multidimensional Models | |
Implementation |
| Default Classes | Description |
| NumModelDataBC::MeanC | |
| NumModelDataBC | Data model implementation class. |
| NumModelDataC | Model that returns mean of samples at given input point. |
| NumModelClosestC | Model that returns Y corresponding to closest X in training data. |
| NumModelClosestBC | Closest model implementation class. |
| NumModelLeastSquareBC | Least squares model fitting implementation class. |
| NumModelPolynomialBC | Polynomial model implementation class. |
| NumModelPolynomialC | Model for fitting n-dimensional polynomials. |
| NumModelQuadraticBC | Quadratic model implementation class. |
| NumModelQuadraticC | Model for fitting second order polynomial with cross parameter terms. |
| NumModelBsplineBC | B-spline model fitting implementation class. |
| NumModelBsplineC | Model for fitting open B-splines. |
| NumModelHybridBsplineBC | Hybrid B-spline model implementation class. |
| NumModelHybridBsplineC | Hybrid model for fitting open B-splines which copes with sparse training data. |
| NumModel2LayerNetC | Two layer feed forward neural network. |
| Author: Anonymous, Generated by DocEntry: March 20, 2001 |