Create a function for plotting Lift Chart?

[hangyao]

I mean a different Lift Chart or classification than the "lift chart" in the cumulative gain curve and lift curve.

Here is a sample: https://medium.com/@inlinecoder/disrupting-the-entrance-point-to-a-predictive-data-analytics-12676aa91a8d https://cran.r-project.org/web/packages/datarobot/vignettes/AdvancedVignette.html

I think this lift chart is quite common in machine learning and data science industry.

I wrote one for binary classification but not sure if it can be extended to multiclass.

def plotLiftChart(actual, predicted):
    df_dict = {'actual': list (actual), 'pred': list(predicted)}
    df = pd.DataFrame(df_dict)
    pred_ranks = pd.qcut(df['pred'].rank(method='first'), 100, labels=False)
    actual_ranks = pd.qcut(df['actual'].rank(method='first'), 100, labels=False)
    pred_percentiles = df.groupby(pred_ranks).mean()
    actual_percentiles = df.groupby(actual_ranks).mean()
    plt.title('Lift Chart')
    plt.plot(np.arange(.01, 1.01, .01), np.array(pred_percentiles['pred']),
             color='darkorange', lw=2, label='Prediction')
    plt.plot(np.arange(.01, 1.01, .01), np.array(pred_percentiles['actual']),
             color='navy', lw=2, linestyle='--', label='Actual')
    plt.ylabel('Target Percentile')
    plt.xlabel('Population Percentile')
    plt.xlim([0.0, 1.0])
    plt.ylim([-0.05, 1.05])
    plt.legend(loc="best")