Gini coefficient of economics and ROC curve machine learning
Receiver Operator curve or ROC curve are used in data mining , machine learning. from area under ROC curve u can calculate Gini coefficient. I have made an excel template
Example to show how its calculated.
if AUC is area under curve then,
G= 2AUC-1
Gini coefficient the most watched coefficient of economics these days :
I wrote a article comparing different countries of world with data available
Gini coefficient AUC has some component of noise which called to question of better measures which are used in machine learning DeltP or informedness ,mattews correlation coefficient each one is suitable to its own field while informedness=1 shows perfect performance while -1 represent perverse of negative performance despite all informedness. Economics Gini zero shows perfect equality.
So parameters keep improving there is no end result and there cannot be as our understanding increases we come at better measures and change is constant..but what is truth today was mystery or magic for old and would be kind of half truth for future..But the subjects are interconnected the branching of knowledge areas is going on since last 250 yrs.. earlier there was no engineering everything was under philosophy during Socrates. Socrates rightly said : that you cannot say anything with absolute certainty. But you can have informed decision that is what informedness quantifies that your decision how much they are informed decisions.
See a case from Biometrics:
Financial Technology Trends 