ec.app.regression.erc.params Maven / Gradle / Ivy

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ECJ, A Java-based Evolutionary Computation Research System. ECJ is a research EC system written in Java. It was designed to be highly flexible, with nearly all classes (and all of their settings) dynamically determined at runtime by a user-provided parameter file. All structures in the system are arranged to be easily modifiable. Even so, the system was designed with an eye toward efficiency. ECJ is developed at George Mason University's ECLab Evolutionary Computation Laboratory. The software has nothing to do with its initials' namesake, Evolutionary Computation Journal. ECJ's sister project is MASON, a multi-agent simulation system which dovetails with ECJ nicely.

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# Copyright 2006 by Sean Luke and George Mason University
# Licensed under the Academic Free License version 3.0
# See the file "LICENSE" for more information

parent.0 = ../../gp/koza/koza.params


# Stolen from koza/params -- overwriting just
# a little for readability
# You need to create at least one function set, 
# called "f0", which your first tree will use.  

gp.fs.size = 1
gp.fs.0.name = f0
gp.fs.0.size = 10
gp.fs.0.func.0 = ec.app.regression.func.X
gp.fs.0.func.0.nc = nc0
gp.fs.0.func.1 = ec.app.regression.func.Add
gp.fs.0.func.1.nc = nc2
gp.fs.0.func.2 = ec.app.regression.func.Mul
gp.fs.0.func.2.nc = nc2
gp.fs.0.func.3 = ec.app.regression.func.Sub
gp.fs.0.func.3.nc = nc2
gp.fs.0.func.4 = ec.app.regression.func.Div
gp.fs.0.func.4.nc = nc2
gp.fs.0.func.5 = ec.app.regression.func.Sin
gp.fs.0.func.5.nc = nc1
gp.fs.0.func.6 = ec.app.regression.func.Cos
gp.fs.0.func.6.nc = nc1
gp.fs.0.func.7 = ec.app.regression.func.Exp
gp.fs.0.func.7.nc = nc1
gp.fs.0.func.8 = ec.app.regression.func.Log
gp.fs.0.func.8.nc = nc1
# placed here at the bottom so noerc.params can skip it
gp.fs.0.func.9 = ec.app.regression.func.RegERC
gp.fs.0.func.9.nc = nc0


#
# We specify our problem here
#

eval.problem = ec.app.regression.Regression
eval.problem.data = ec.app.regression.RegressionData

# The size of our training set, by default, is 20
eval.problem.size = 20