Lorenz curve is a visual representation of inequality. It is used to measure the discriminatory power of the predictive model.
blr_lorenz_curve( model, data = NULL, title = "Lorenz Curve", xaxis_title = "Cumulative Events %", yaxis_title = "Cumulative Non Events %", diag_line_col = "red", lorenz_curve_col = "blue", print_plot = TRUE )
model | An object of class |
---|---|
data | A |
title | Plot title. |
xaxis_title | X axis title. |
yaxis_title | Y axis title. |
diag_line_col | Diagonal line color. |
lorenz_curve_col | Color of the lorenz curve. |
print_plot | logical; if |
Other model validation techniques:
blr_confusion_matrix()
,
blr_decile_capture_rate()
,
blr_decile_lift_chart()
,
blr_gains_table()
,
blr_gini_index()
,
blr_ks_chart()
,
blr_roc_curve()
,
blr_test_hosmer_lemeshow()
model <- glm(honcomp ~ female + read + science, data = hsb2, family = binomial(link = 'logit')) blr_lorenz_curve(model)