Contents
What is Gini coefficient model performance?
The Gini coefficient is defined as the ratio between the area within the model curve and the random model line (A) and the area between the perfect model curve and the random model line (A+B).
Which metric is right for model performance evaluation?
Root Mean Squared Error (RMSE) RMSE is the most popular evaluation metric used in regression problems.
What is Gini coefficient in Analytics?
The Gini Coefficient or Gini Index measures the inequality among values of a variable. Higher the value of an index, more dispersed is the data. Alternatively, the Gini coefficient can be looked like half of the relative mean absolute difference. It is a very popular measure in econometric studies.
What is a good Gini value?
It is influenced by the distribution of income between people. Gini index < 0.2 represents perfect income equality, 0.2–0.3 relative equality, 0.3–0.4 adequate equality, 0.4–0.5 big income gap, and above 0.5 represents severe income gap. The Gini coefficient is a measure of inequality of a distribution.
How is the Gini coefficient used in the real world?
This metric is often used to compare the quality of different models and evaluate their prediction power. Despite its commonality, some practitioners are not genuinely familiar with the mechanism beyond this Gini coefficient and mistakenly confuse it with a different metric with the same name.
How is the Gini metric used in logistic regression?
The model is a Logistic Regression estimator and was built by another team. They use the Gini metric to measure the performance of the model. They achieved 87%. Upon evaluation, I found that the recall was 51% whilst the error rate of the non rare event class (do not default) was 0.9%.
Why is Gini not a good predictor of defaults?
This has nothing to do with our success at predicting individual defaults, which is why the Gini is not really useful. Because the costs and profit numbers are specific to each lender, it is quite possible that Model A will work better than Model B for one lender, while Model B will work better than Model A for another lender.
Do you disclose the AUC with the Gini coefficient?
Practitioners tend to disclose the AUC in addition to the Gini coefficient in their model validation report. However, since these metrics have a linear relation, the disclosure of these metrics together doesn’t add any value to the evaluation of the model’s quality.