












• 
Suppose you have
a weak learning module (a “base



classifier”)
that can always get 0.5+epsilon correct when



given a twoway
classification task




– 
That
seems like a weak assumption but beware!



• 
Can you apply
this learning module many times to get a



strong learner
that can get close to zero error rate on the


training data?




– 
Theorists
showed how to do this and it actually led to



an
effective new learning procedure (Freund &



Shapire,
1996)

