Decision Tree Pruning Algorithm

A Decision Tree Pruning Algorithm is a model complexity and error reduction algorithm that accepts a decision tree.

• Context:
  • It can range from being a Decision Tree Pre-Pruning Algorithm to being a Decision Tree Post-Pruning Algorithm.
  • It can range from being a Classification Tree Pruning Algorithm, to being a Ranking Tree Pruning Algorithm, to being a Regression Tree Pruning Algorithm.
  • It can (typically) be applied by a Decision Tree Learning System (as part of a Decision Tree Learning Algorithm).
  • …
• Counter-Example(s):
  • a Decision Tree Splitting Criterion.
  • an Alpha-Beta Pruning Algorithm.
• See: Machine Learning Algorithm.

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References

2013

• http://en.wikipedia.org/wiki/Pruning_%28decision_trees%29
  • Pruning is a technique in machine learning that reduces the size of decision trees by removing sections of the tree that provide little power to classify instances. The dual goal of pruning is reduced complexity of the final classifier as well as better predictive accuracy by the reduction of overfitting and removal of sections of a classifier that may be based on noisy or erroneous data.

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