visual.py 文件源码

def plot_cumulative_gains(lift: pd.DataFrame):
    fig, ax = plt.subplots()
    fig.canvas.draw()

    handles = []
    handles.append(ax.plot(lift['PercentCorrect'], 'r-', label='Percent Correct Predictions'))
    handles.append(ax.plot(lift['PercentCorrectBestCase'], 'g-', label='Best Case (for current model)'))
    handles.append(ax.plot(lift['PercentAvgCase'], 'b-', label='Average Case (for current model)'))
    ax.set_xlabel('Total Population (%)')
    ax.set_ylabel('Number of Respondents (%)')

    ax.set_xlim([0, 9])
    ax.set_ylim([10, 100])
    try:
        labels = [int((label+1)*10) for label in [float(item.get_text()) for item in ax.get_xticklabels() if len(item.get_text()) > 0]]
    except BaseException as e:
        print([item.get_text() for item in ax.get_xticklabels()])

    ax.set_xticklabels(labels)

    fig.legend(handles, labels=[h[0].get_label() for h in handles])
    fig.show()