Fast Forest Quantile Regression

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Quantile regression is useful if you want to understand more about the distribution of the predicted value, rather than get a single mean prediction value. This method has many applications, including:

• Predicting prices
• Estimating student performance or applying growth charts to assess child development
• Discovering predictive relationships in cases where there is only a weak relationship between variables

This regression algorithm is a supervised learning method, which means it requires a tagged dataset that includes a label column. Because it is a regression algorithm, the label column must contain only numerical values.. Fast Forest Quantile Regression | Microsoft