visualization.py 文件源码

def visualize_pca2D(X,y):
    """
    Visualize the first two principal components

    Keyword arguments:
    X -- The feature vectors
    y -- The target vector
    """
    pca = PCA(n_components = 2)
    principal_components = pca.fit_transform(X)

    palette = sea.color_palette()
    plt.scatter(principal_components[y==0, 0], principal_components[y==0, 1], marker='s',color='green',label="Paid", alpha=0.5,edgecolor='#262626', facecolor=palette[1], linewidth=0.15)
    plt.scatter(principal_components[y==1, 0], principal_components[y==1, 1], marker='^',color='red',label="Default", alpha=0.5,edgecolor='#262626''', facecolor=palette[2], linewidth=0.15)

    leg = plt.legend(loc='upper right', fancybox=True)
    leg.get_frame().set_alpha(0.5)
    plt.title("Two-Dimensional Principal Component Analysis")
    plt.tight_layout

    #save fig
    output_dir='img'
    save_fig(output_dir,'{}/pca2D.png'.format(output_dir))