# Fast Forest Quantile Regression

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- Fast Forest Quantile Regression | Microsoft
- 5 Regression Loss Functions All Machine Learners Should Know - Choosing the right loss function for fitting a model | Prince Grover
- Loss Functions

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..