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1.4. Support Vector Machines — scikit-learn 0.23.2 documentation s include: If the number of features is much greater than the number of samples, avoid over-fitting in choosing Kernel functions and regularization term is crucial. SVMs do not directly provide <span>probability estimates, these are calculated using an expensive five-fold cross-validation (see Scores and probabilities, below). The support vector machines in scikit-learn support both dense (numpy.ndarray
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