@@ -287,7 +287,7 @@ def predict(np.ndarray[np.float64_t, ndim=2, mode='c'] X,
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Parameters
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----------
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- X: array-like, dtype=float, size=[n_samples, n_features]
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+ X : array-like, dtype=float, size=[n_samples, n_features]
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svm_type : {0, 1, 2, 3, 4, 5}
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Type of SVM: C SVC, nu SVC, one class, epsilon SVR, nu SVR,
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or SVDD-L1.
@@ -364,7 +364,7 @@ def predict_proba(
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Parameters
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----------
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- X: array-like, dtype=float
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+ X : array-like, dtype=float
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kernel : {'linear', 'rbf', 'poly', 'sigmoid', 'precomputed'}
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Returns
@@ -478,9 +478,9 @@ def cross_validation(
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Parameters
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----------
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- X: array-like, dtype=float, size=[n_samples, n_features]
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+ X : array-like, dtype=float, size=[n_samples, n_features]
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- Y: array, dtype=float, size=[n_samples]
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+ Y : array, dtype=float, size=[n_samples]
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target vector
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svm_type : {0, 1, 2, 3, 4, 5}
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