December 2017
Intermediate to advanced
386 pages
10h 42m
English
This represents the final result of the method:

For regression from the point of view of curve fitting, there is a generic curve_fit routine in the scipy.optimize module.
This routine minimizes the sum of squares of a set of equations using the Levenberg-Marquardt algorithm and offers a best fit from any kind of functions (not only polynomials or splines). The syntax is simple:
curve_fit(f, xdata, ydata, p0=None, sigma=None, **kw)
The f parameter is a callable function that represents the function we seek, and xdata and ydata are arrays of the same length that contain the x and y coordinates of the points to be fit. The p0 ...
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