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The demo creates a random forest regression model, evaluates the model accuracy on the training and test data, and then uses the model to predict the target y value for x = [-0.1660, 0.4406, -0.9998, ...
Among these three regression models, random forest regression has the best prediction effect with a model score of 0.8564, which is the best prediction effect among the three models.
In multi-target regression, models are designed to predict a vector of continuous responses rather than a single outcome, thereby capturing the often intricate interdependencies among targets.