Suppose that a learning algorithm is trying to find a consistent hypothesis

WRITE MY PAPER

 
Suppose that a learning algorithm is trying to find a consistent hypothesis when the classifications of examples are actually random. There are n Boolean attributes, and examples are drawn uniformly from the set of 2^n possible examples. Calculate the number of examples required before the probability of finding a contradiction in the data reaches 0.5. 

WRITE MY PAPER

Leave a Comment

Your email address will not be published. Required fields are marked *

Scroll to Top