svm

References/Python/scikit-learn/API Reference/svm

class sklearn.svm.SVC(C=1.0, kernel='rbf', degree=3, gamma='auto', coef0=0.0, shrinking=True, probability=False, tol=0.001, cache_size=200, class_weight=None

2025-01-10 15:47:30

svm.LinearSVC()

References/Python/scikit-learn/API Reference/svm

class sklearn.svm.LinearSVC(penalty='l2', loss='squared_hinge', dual=True, tol=0.0001, C=1.0, multi_class='ovr', fit_intercept=True, intercept_scaling=1

2025-01-10 15:47:30

sklearn.svm.libsvm.predict_proba()

References/Python/scikit-learn/API Reference/svm

sklearn.svm.libsvm.predict_proba() Predict probabilities svm_model stores all parameters needed to

2025-01-10 15:47:30

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