Developer Guide for Intel® Data Analytics Acceleration Library 2018

Details

Given:

The problem is to build a regression decision tree.

Split Criterion

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 to be used in the node is selected as . For binary decision tree with 'true' and 'false' branches,

Training Stage

The regression decision tree follows the algorithmic framework of decision tree training described in Classification and Regression > Decision tree >Training stage.

Prediction 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.