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Class sim.errFun.PDFE

java.lang.Object
   |
   +----sim.errFun.ErrFun
           |
           +----sim.errFun.PDFE

public class PDFE
extends ErrFun
Run the PDF Emulation algorithm to model an arbitrary PDF using an arbitrary function approximator. and gradient-descent algorithm.

This code is (c) 1996,1997 Leemon Baird <leemon@cs.cmu.edu>, http://www.cs.cmu.edu/~baird
The source and object code may be redistributed freely. If the code is modified, please state so in the comments.

Version:
1.1, 21 July 97
Author:
Leemon Baird

Constructor Index

 o PDFE()

Method Index

 o BNF(int)
Return the BNF description of how to parse the parameters of this object.
 o evaluate(Random, boolean, boolean, boolean)
return the scalar output for the current weight vector x.
 o findGradient()
update the fGradient vector based on the dEdOutput.
 o parse(Parser, int)
Parse the input file to get the parameters for this object.
 o setWatchManager(WatchManager, String)
Register all variables with this WatchManager.
 o unparse(Unparser, int)
Output a description of this object that can be parsed with parse().

Constructors

 o PDFE
 public PDFE()

Methods

 o setWatchManager
 public void setWatchManager(WatchManager wm,
                             String name)
Register all variables with this WatchManager. This will be called after all parsing is done. setWatchManager should be overridden and forced to call the same method on all the other objects in the experiment.

Overrides:
setWatchManager in class ErrFun
 o BNF
 public String BNF(int lang)
Return the BNF description of how to parse the parameters of this object.

Overrides:
BNF in class ErrFun
 o unparse
 public void unparse(Unparser u,
                     int lang)
Output a description of this object that can be parsed with parse().

Overrides:
unparse in class ErrFun
See Also:
Parsable
 o parse
 public Object parse(Parser p,
                     int lang) throws ParserException
Parse the input file to get the parameters for this object.

Throws: ParserException
parser didn't find the required token
Overrides:
parse in class ErrFun
 o evaluate
 public double evaluate(Random rnd,
                        boolean willFindDeriv,
                        boolean willFindHess,
                        boolean rememberNoise)
return the scalar output for the current weight vector x. err=g(x-f(v)) + g(x-f(v')) - g(f(v)-f(v'))

Overrides:
evaluate in class ErrFun
 o findGradient
 public void findGradient()
update the fGradient vector based on the dEdOutput. err=g(x-f(v)) + g(x-f(v')) - g(f(v)-f(v')) return gradient of err wrt weights.

Overrides:
findGradient in class ErrFun

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