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Line search fails in two-class probability estimates
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Model doesn't contain information for SVR probability inference
Invalid input - all samples with positive weights have the same label.Invalid input - all samples have zero or negative weights.degree of polynomial kernel < 0shrinking != 0 and shrinking != 1probability != 0 and probability != 1one-class SVM probability output not supported yetProb. model for test data: target value = predicted value + z,
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    X : array-like, dtype=float
    Y : array
        target vector

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    Wrap svm_train from libsvm using a scipy.sparse.csr matrix

    Work in progress.

    Parameters
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    n_features : number of features.
        XXX: can we retrieve this from any other parameter ?

    X : array-like, dtype=float, size=[N, D]

    Y : array, dtype=float, size=[N]
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    See sklearn.svm.predict for a complete list of parameters.

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