Trained Class Prediction Tree

A Trained Class Prediction Tree is a trained prediction tree (composed of nodes and edges) that is a classification point estimator.

• Context:
  • It can (typically) be produced by a Classification Tree Training System (that solves a classification tree training task).
  • It can be pruned by a Classification Tree Post-Pruning Algorithm.
• Example(s):
  • A Binary-Class Prediction Tree, such as:
    IF A>4 THEN
      (IF B=0 THEN yes/76%:no/24% ELSE no/63%:no/37%)
ELSE yes/81%:no/19%
  • a Multiclass Prediction Tree, such as:
  • one created from a Iris Dataset.
  • …
• Counter-Example(s):
  • a Trained Regression Tree.
  • a Trained Ranking Tree.
  • a Trained Naive Bayes Classifier.
  • a Trained Logistic Regression Classifier.
  • a Trained SVM Classifier.
• See: PMML Tree, Piecewise Constant Regression Model, Tree-based Function.

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