如何找出在sklearn SVC中哪些支持向量属于哪个类？
model = clf.fit(X,y) vectors = model.support_vectors_哪些向量属于哪个决策边界？
回答：
您可以使用SVC.support_属性。support_属性提供了SVC.support_vectors_中每个支持向量的训练数据的索引。您可以按如下方式检索每个支持向量的类别（基于您的示例）：
X[model.support_]更完整的示例：
import numpy as npimport matplotlib.pyplot as pltfrom matplotlib.colors import ListedColormapfrom sklearn.model_selection import train_test_splitfrom sklearn.preprocessing import StandardScalerfrom sklearn.datasets import make_classificationfrom sklearn.svm import SVCsvc = SVC(kernel='linear', C=0.025)X, y = make_classification(n_samples=500, n_features=2, n_redundant=0, n_informative=2, random_state=1, n_clusters_per_class=1)rng = np.random.RandomState(2)X += 2 * rng.uniform(size=X.shape)X = StandardScaler().fit_transform(X)X_tr, X_te, y_tr, y_te = train_test_split(X, y, test_size=.4, random_state=42)cm_bright = ListedColormap(['#FF0000', '#0000FF'])fig, ax = plt.subplots(figsize=(18,12))ax.scatter(X_tr[:, 0], X_tr[:, 1], c=y_tr, cmap=cm_bright)svc.fit(X_tr, y_tr)y_tr[svc.support_]array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])fig2, ax2 = plt.subplots(figsize=(18,12))ax2.scatter(X_tr[:, 0], X_tr[:, 1], c=y_tr, cmap=cm_bright)ax2.scatter(svc.support_vectors_[:, 0], svc.support_vectors_[:, 1]) fig3, ax3 = plt.subplots(figsize=(18,12))ax3.scatter(X_tr[:, 0], X_tr[:, 1], c=y_tr, cmap=cm_bright)ax3.scatter(svc.support_vectors_[:, 0], svc.support_vectors_[:, 1], c=y_tr[svc.support_], cmap=cm_bright)
