![]() ![]() Random forest uses gini importance or mean decrease in impurity (MDI) to calculate the importance of each feature. This score will help to choose the most important features and drop the least important ones for model building. Then it scales the relevance down so that the sum of all scores is 1. It automatically computes the relevance score of each feature in the training phase. Scikit-learn provides an extra variable with the random forest model, which shows the relative importance or contribution of each feature in the prediction. The random forest also offers a good feature selection indicator.
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