svm import SVC model = SVC(kernel='rbf', probability=True) param_grid = {'C': [1e-3, 1e-2, 1e-1, 1, 10, 100, 1000], 'gamma': [0.001, 0.0001]} grid_search = GridSearchCV(model, param_grid, n_jobs = 1, verbose=1) grid_search.fit(train_x, train_y) best_parameters ...
# 绘制,第一个二分类器的分割超平面w = clf.coef_[0]a = -w[0] / w[1]# a可以理解为斜率xx = np.linspace(-5, 5)yy = a * xx - clf.intercept_[0] / w[1]# 二维坐标下的直线方程 # 使用类权重,获取分割超平面wclf = svm.SVC(kernel='linear', class_weight={1: 10})wclf.fit(X,...