Discovering Time Oriented Abstractions in Historical Data to Optimize Decision Tree Classification
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InCollection{masand:1996:aigp2,
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author = "Brij Masand and Gregory Piatesky-Shapiro",
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title = "Discovering Time Oriented Abstractions in Historical
Data to Optimize Decision Tree Classification",
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booktitle = "Advances in Genetic Programming 2",
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publisher = "MIT Press",
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year = "1996",
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editor = "Peter J. Angeline and K. E. {Kinnear, Jr.}",
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pages = "489--498",
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chapter = "24",
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address = "Cambridge, MA, USA",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "0-262-01158-1",
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URL = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6277523",
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DOI = "doi:10.7551/mitpress/1109.003.0031",
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size = "10 pages",
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abstract = "This paper explores the synergy between OP and
decision tree-based classification. We are addressing
the problem of identifying 'good' customers (e.g those
who respond to special offers) by analysing historical
customer billing data, using decision tree classifiers
such as C4.5 [Quinlan 1993) and optimising that
performance using OP [Koza 1992]. One difficult issue
is how to transform and abstract raw historical data
from several months for the purpose of analysis. We ad
dress this by using OP to discover time oriented data
abstractions of data. that enable improved prediction
performance. than possible with the raw data alone. We
also contrast the performance improvement obtained by
generating random populations with comparable
computational effort vs. OP evolution on smaller
populations. Using C4.5 alone we are able to get a
prediction error of about 38percent (on a 50-50percent
test set of non-responders/responders) Using the
additional derived fields from raw billing data, we are
able to reduce the error to 35.9percent, a significant
reduction for this domain. Each 1percent of improved
performance (on real data) is worth about $1 million in
potential increased revenues.",
- }
Genetic Programming entries for
Brij Masand
Gregory Piatesky-Shapiro
Citations