Improving Induction of Linear Classification Trees with Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8129
- @InProceedings{Bot:2000:GECCO,
-
author = "Martijn C. J. Bot",
-
title = "Improving Induction of Linear Classification Trees
with Genetic Programming",
-
pages = "403--410",
-
year = "2000",
-
publisher = "Morgan Kaufmann",
-
booktitle = "Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO-2000)",
-
editor = "Darrell Whitley and David Goldberg and
Erick Cantu-Paz and Lee Spector and Ian Parmee and Hans-Georg Beyer",
-
address = "Las Vegas, Nevada, USA",
-
publisher_address = "San Francisco, CA 94104, USA",
-
month = "10-12 " # jul,
-
keywords = "genetic algorithms, genetic programming",
-
ISBN = "1-55860-708-0",
-
URL = "http://gpbib.cs.ucl.ac.uk/gecco2000/GP185.pdf",
-
URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/martijn/bot.gecco2000.19jan.ps.gz",
-
URL = "http://citeseer.ist.psu.edu/316984.html",
-
abstract = "Decision trees are a well known technique in machine
learning for describing the underlying structure of a
dataset. In [Bot and Langdon, 2000] a new
representation of decision trees using strong typing in
GP was introduced. In the function nodes, a linear
combination of variables is made. The effects of
techniques such as limited error fitness, fitness
sharing Pareto scoring and domination Pareto scoring
are evaluated on a set of benchmark classification
problems. Comparisons with current state-of-the-art
algorithms in machine learning are presented and areas
of future research are identified. Results indicate
that GP can be applied successfully to classification
problems. Limited error fitness reduces runtime while
maintaing equal accuracy. Pareto scoring works well
against bloat. Fitness sharing Pareto works better than
domination Pareto.",
-
notes = "A joint meeting of the ninth International Conference
on Genetic Algorithms (ICGA-2000) and the fifth Annual
Genetic Programming Conference (GP-2000) Part of
\cite{whitley:2000:GECCO}",
- }
Genetic Programming entries for
Martijn C J Bot
Citations