Train Gradient-Boosted Trees to Predict Wind Speed
Gradient-boosted trees is a classification and regression method that excels on structured datasets. This example shows how to use this method on a regression example.
Load a dataset of wind speed measurements at various locations, and keep a few test data points.
Learn to predict the value of the wind speed in "RochesPoint" as a function of other wind speeds using gradient-boosted trees.
Obtain generic information about the predictor.
Obtain specific information about the hyperparameters selected by the automation procedure.
Predict values for the examples in the test set.
Compare the predicted values with the measured values.
Perform another training and specify the value of the "BoostingMethod" hyperparameter (see "GradientBoostedTrees" for a complete list of hyperparameters).
Compare the predicted values with the measured values.
