26 Decision tree

Decision Trees

Method of organizing decisions over time in the face of uncertainties.

How to Create a Tree

Create the tree, one node at a time

  • Decision nodes and event nodes
  • Probabilities: usually subjective
  • Solve the tree by working backwards, starting with the end nodes.
  • Often we minimize expected cost (or maximize gain).

Classification Trees

  • Data consisting of learning set of cases
  • Each case consists of a set of attributes with values and has a known class
  • Classes are one of a small number of possible values, usually binary
  • Attributes may be binary, multivalued, or continuous

Example

 

 

Python 3 Example: Please click here to see the Python3 Example.

 

Resources for this chapter

https://ocw.mit.edu/courses/sloan-school-of-management/15-053-optimization-methods-in-management-science-spring-2013/lecture-notes/MIT15_053S13_lec18.pdf

https://ocw.mit.edu/courses/health-sciences-and-technology/hst-951j-medical-decision-support-spring-2003/lecture-notes/lecture10.pdf

License

Building Skills for Data Science Copyright © by Dr. Nouhad Rizk. All Rights Reserved.

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