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What is the Gini Coefficient and why is it used in a binary classification scenario? |
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Answer» Response: Gini Coefficient is a measure to USE feature importance in a random forest algorithm. In a binary classification scenario, when we are predicting both classes, the Gini coefficient can be computed based on AUC (Area Under the Curve) value. It measures the inequality between values of a frequency distribution. It is computed as the following: Gini Coeff (Gini Coefficient) = 2 * AUC – 1 Link REFERENCE: In the above example and FIGURE 25, Gini Coeff = A / (A+B). |
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