Summary Combining Inductive and Analytical Learning

Combining Inductive and Analytical
Learning

[Read Ch. 12]
[Suggested exercises: 12.1, 12.2, 12.6, 12.7, 12.8]
 Why combine inductive and analytical learning?
 KBANN: Prior knowledge to initialize the
hypothesis
 TangetProp, EBNN: Prior knowledge alters
search objective
 FOCL: Prior knowledge alters search operators




1 lecture slides for textbook Machine Learning, c T. Mitchell, McGraw Hill, 1997

, Inductive and Analytical Learning

Inductive learning Analytical learning
Hypothesis ts data Hypothesis ts domain th
Statistical inference Deductive inference
Requires little prior knowledge Learns from scarce data
Syntactic inductive bias Bias is domain theory




2 lecture slides for textbook Machine Learning, c T. Mitchell, McGraw Hill, 1997

, What We Would Like

Inductive learning Analytical learning
Plentiful data Perfect prior knowledge
No prior knowledge Scarce data


General purpose learning method:
 No domain theory ! learn as well as inductive
methods
 Perfect domain theory ! learn as well as
Prolog-EBG

 Accomodate arbitrary and unknown errors in
domain theory
 Accomodate arbitrary and unknown errors in
training data




3 lecture slides for textbook Machine Learning, c T. Mitchell, McGraw Hill, 1997