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Unformatted text preview: 1 Foundations of Artificial Intelligence Instance-Based Learning CS472 – Fall 2007 Thorsten Joachims What is Learning? • Examples – Riding a bike (motor skills) – Telephone number (memorizing) – Read textbook (memorizing and operationalizing rules) – Playing backgammon (strategy) – Develop scientific theory (abstraction) – Language – Recognize fraudulent credit card transactions – Etc. (One) Definition of Learning Definition [Mitchell]: A computer program is said to learn from • experience E with respect to some class of • tasks T and • performance measure P, if its performance at tasks in T, as measured by P, improves with experience E. Examples • Spam Filtering – T: Classify emails HAM / SPAM – E: Examples (e 1 ,HAM),(e 2 ,SPAM),(e 3 ,HAM),(e 4 ,SPAM), ... – P: Prob. of error on new emails • Personalized Retrieval – T: find documents the user wants for query – E: watch person use Google (queries / clicks) – P: # relevant docs in top 10 • Play Checkers – T: Play checkers – E: games against self – P: percentage wins How can an Agent Learn? Learning strategies and settings • rote learning • learning from instruction • learning by analogy • learning from observation and discovery • learning from examples –Carbonell, Michalski & Mitchell. Inductive Learning / Concept Learning • Task: – Learn (to imitate) a function f: X Æ Y • Training Examples: – Learning algorithm is given the correct value of the function for particular inputs Æ...
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This note was uploaded on 02/19/2008 for the course CS 4700 taught by Professor Joachims during the Fall '07 term at Cornell.
- Fall '07
- Artificial Intelligence