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Monotonicity Hints Joseph Sill
 

Summary: Monotonicity Hints
Joseph Sill
Computation and Neural Systems program
California Institute of Technology
email: joe@cs.caltech.edu
Yaser S. Abu­Mostafa
EE and CS Deptartments
California Institute of Technology
email: yaser@cs.caltech.edu
Abstract
A hint is any piece of side information about the target function to
be learned. We consider the monotonicity hint, which states that
the function to be learned is monotonic in some or all of the input
variables. The application of monotonicity hints is demonstrated
on two real­world problems­ a credit card application task, and a
problem in medical diagnosis. A measure of the monotonicity error
of a candidate function is defined and an objective function for the
enforcement of monotonicity is derived from Bayesian principles.
We report experimental results which show that using monotonicity
hints leads to a statistically significant improvement in performance

  

Source: Abu-Mostafa, Yaser S. - Department of Mechanical Engineering & Computer Science Department, California Institute of Technology

 

Collections: Computer Technologies and Information Sciences