Current Slide

Small screen detected. You are viewing the mobile version of SlideWiki. If you wish to edit slides you will need to use a larger device.


  • Machine learning is a prominent topic in the field of AI.
  • Rule learning is a means to learn rules from instance data to classify unseen instances.
  • Decision tree learning can be used for concept learning, rule learning, or for learning of other discrete valued functions.
  • The ID3 family of algorithms infers decision trees by growing them from the root downward in a greedy manner.
  • ID3 searches a complete hypothesis space.
  • ID3’s inductive bias includes a preference for smaller trees; it grows trees only as large as needed.
  • A variety of extensions to basic ID3 have been developed; extensions include: methods for post-pruning trees, handling real-valued attributes, accommodating training examples with missing attribute values, or using alternative selection measures.

Speaker notes:

Content Tools


There are currently no sources for this slide.