The example in is very hard to understand. Result = sp.optimize.minimize(square_error)īut I don't know how to add constrains in minimize method. The code is like this: from sklearn.neighbors import KernelDensityĭef gaussian_2d(x,y,meanx,meany,sigx,sigy,rho): ![]() I have a dataset, and I'd like to find a mixed gaussian model by least square error method.
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