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Showing content from http://scikit-learn.sourceforge.net/dev/developers/../modules/generated/sklearn.svm.NuSVR.html below:

sklearn.svm.NuSVR — scikit-learn 0.17.dev0 documentation

C : float, optional (default=1.0)

Penalty parameter C of the error term.

nu : float, optional

An upper bound on the fraction of training errors and a lower bound of the fraction of support vectors. Should be in the interval (0, 1]. By default 0.5 will be taken.

kernel : string, optional (default=’rbf’)

Specifies the kernel type to be used in the algorithm. It must be one of ‘linear’, ‘poly’, ‘rbf’, ‘sigmoid’, ‘precomputed’ or a callable. If none is given, ‘rbf’ will be used. If a callable is given it is used to precompute the kernel matrix.

degree : int, optional (default=3)

Degree of the polynomial kernel function (‘poly’). Ignored by all other kernels.

gamma : float, optional (default=’auto’)

Kernel coefficient for ‘rbf’, ‘poly’ and ‘sigmoid’. If gamma is ‘auto’ then 1/n_features will be used instead.

coef0 : float, optional (default=0.0)

Independent term in kernel function. It is only significant in ‘poly’ and ‘sigmoid’.

shrinking : boolean, optional (default=True)

Whether to use the shrinking heuristic.

tol : float, optional (default=1e-3)

Tolerance for stopping criterion.

cache_size : float, optional

Specify the size of the kernel cache (in MB).

verbose : bool, default: False

Enable verbose output. Note that this setting takes advantage of a per-process runtime setting in libsvm that, if enabled, may not work properly in a multithreaded context.

max_iter : int, optional (default=-1)

Hard limit on iterations within solver, or -1 for no limit.


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