Gini coefficient is sometimes used in classification problems. Gini coefficient can be straigh away derived from the AUC ROC number. Gini is nothing but ratio between area between the ROC curve and the diagnol line & the area of the above triangle. Following is the formulae used :
Gini = 2*AUC – 1
Gini above 60% is a good model. For the case in hand we get Gini as 92.7%.
The Gini Coefficient:
i) Also known as the Gini index or Gini ratio.
ii) It is a measure of of statistical dispersion intended to represent the income inequality or or wealth inequality.
iii) The coefficient measures the dispersion of income.
iv) The coefficient can take any values between 0 to 1 (or 0% to 100%).
v) A coefficient of zero indicates a perfectly equal distribution of income or wealth.
vi) The Gini coefficient was proposed by Gini as a measure of inequality of income or wealth.