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The bump hunting method and its accuracy using
the genetic algorithm with application to real customer data
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Hirose, H., Yukizane,T., and Deguchi, T.
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IEEE 7th International Conference on Computer and Information
Technology 2007 (CIT2007), pp.128-132, October 16-19, 2007, Aizu
University
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Suppose
that we are interested in searching for denser regions showing
response 1 with many feature variables (explanation variables)
in a z-dimensional space, where each point is assigned response
1 or response 0 as its target value; such a region is called the
bump. In a series of previous studies, we have shown that the bump
hunting method using the decision tree combined with the genetic
algorithm is useful for certain smaller simulated data case mimicked
to a real customer case. We have developed a trade-off curve with
its accuracy evaluation between the pureness rate and the capture
rate to the simulated data. This paper deals with a real customer
data case, and we have found that it is crucial to know the relation
between the number of feature variables and the number of samples. |
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Application
software , Decision trees , Genetic algorithms , Information
technology , Search methods , Shape , Space technology ,
Statistics , Training data , Tree data structures |
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@
Times Cited in Web of Science:
Times Cited in Google Scholar: 4
Cited in Books:
WoS:
Others:
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