figure.classification.vs.regression.py 文件源码

def make_classification_example(axis, random_state):
    X, y = make_blobs(n_samples=100, n_features=2, centers=2, cluster_std=2.7, random_state=random_state)

    axis.scatter(X[y == 0, 0], X[y == 0, 1], color="red", s=10, label="Disease")
    axis.scatter(X[y == 1, 0], X[y == 1, 1], color="blue", s=10, label="Healthy")

    clf = LinearSVC().fit(X, y)

    # get the separating hyperplane
    w = clf.coef_[0]
    a = -w[0] / w[1]
    xx = np.linspace(-5, 7)
    yy = a * xx - (clf.intercept_[0]) / w[1]

    # plot the line, the points, and the nearest vectors to the plane
    axis.plot(xx, yy, 'k-', color="black", label="Model")

    ax1.tick_params(labelbottom='off', labelleft='off')
    ax1.set_xlabel("Gene 1")
    ax1.set_ylabel("Gene 2")
    ax1.legend()