Developer Guide for Intel® Data Analytics Acceleration Library 2019 Update 4
Given:
The problem is to build a regression decision tree.
The library provides the decision tree regression algorithm based on the mean-squared error (MSE) [Breiman84].:
Where
O( τ ) is the set of all possible outcomes of test τ
D
v
is the subset of
D, for which outcome of
τ
is
v, for example,
.
The test used in the node is selected as
. For binary decision tree with "true" and "false" branches,
The regression decision tree follows the algorithmic framework of decision tree training described in Classification and Regression > Decision tree >Training stage.
The regression decision tree follows the algorithmic framework of decision tree prediction described in Classification and Regression > Decision tree > Prediction stage.
Given the regression decision tree and vectors x 1, …, x r , the problem is to calculate the responses for those vectors.