我正在尝试为用LinearSVC和sklearn训练的模型绘制超平面。请注意，我正在使用自然语言。在拟合模型之前，我使用CountVectorizer和TfidfTransformer提取了特征。
这里是分类器：
from sklearn.svm import LinearSVC
from sklearn import svm
clf = LinearSVC(C=0.2).fit(X_train_tf, y_train)
然后我尝试按照Scikit-learn网站上的建议进行绘图：
# get the separating hyperplane
w = clf.coef_[0]
a = -w[0] / w[1]
xx = np.linspace(-5, 5)
yy = a * xx - (clf.intercept_[0]) / w[1]
# plot the parallels to the separating hyperplane that pass through the
# support vectors
b = clf.support_vectors_[0]
yy_down = a * xx + (b[1] - a * b[0])
b = clf.support_vectors_[-1]
yy_up = a * xx …