A regression tree uses sum of squares and regression analysis to predict target field values.
Predictions are based on combinations of values in input fields.
A regression tree calculates an average predicted value for each node in the tree.
This type of tree is generated when the target field is continuous.
Building a decision tree starts with the root node, which is all the rows in the data.
All nodes are split into child nodes until the sum of squares can no longer be improved or the number of rows of data corresponding to the node is too low.
The creation of a decision tree also stops if the number of nodes in the decision tree is too high.
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