![]() Numerical Recipes in FORTRAN 77 W.H.Press, S.A.Teukolsky, W.T.Vetterling, B.P. Lagrange Interpolating Polynomial is a method for finding the equation corresponding to a curve having some dots. Below given is the program which involves fitting linear and cubic polynomial curves to a given data set FITTING LINEAR AND CUBIC POLYNOMIALS FOR A GIVEN. Aim: Scilab program for lagrange polynomial interpolation / X 1 2 5 10 //set the arguments Y 10 75 100 12 //set the corresponding values of f (x) nlength (X) // store the length of total arguments x. This example shows that you can do non-linear regression with a linear model, using a pipeline to add non-linear features. The matrix is akin to (but different from) the matrix induced by a polynomial kernel. H�D���0ō��4�zw�Pt��]͋j|�����0�(\�I�w⬞�67 A��ԣm������q�O>5Įndstreamendobj14628 0 obj/ProcSet>/Subtype/Form/FormType 1/Matrix/Group>streamĮndstreamendobj14629 0 obj/ProcSet/ExtGState>/Subtype/Form/FormType 1/Matrix>stream The following is the source code of scilab program for polynomial interpolation by numerical method known as lagrange interpolation. Intuitively, this matrix can be interpreted as a matrix of pseudo features (the points raised to some power). ![]()
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