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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")
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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.
The text was updated successfully, but these errors were encountered: