A hierarchical estimation of multi-modal distribution programming for regression problems
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- @Article{KOOSHA:2023:knosys,
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author = "Mohaddeseh Koosha and Ghazaleh Khodabandelou and
Mohammad Mehdi Ebadzadeh",
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title = "A hierarchical estimation of multi-modal distribution
programming for regression problems",
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journal = "Knowledge-Based Systems",
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volume = "260",
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pages = "110129",
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year = "2023",
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ISSN = "0950-7051",
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DOI = "doi:10.1016/j.knosys.2022.110129",
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URL = "https://www.sciencedirect.com/science/article/pii/S0950705122012254",
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keywords = "genetic algorithms, genetic programming, Estimation of
distribution programming, Program Trees, Regression",
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abstract = "Estimation of distribution programming is an iterative
method to evolve program trees. It estimates the
distribution of the most suitable program trees and
then produces a new generation of program trees by
sampling from the distribution. This paper proposes a
hierarchical estimation of multimodal distribution
programming (HEMMDP). First, the population is divided
into K subpopulations by a clustering algorithm where
the distribution of each subpopulation is modified
according to an objective function. Then, at each
generation, a new subpopulation is generated from the
modified distribution. The objective function aims to
gradually improve the fitness of the program trees in
each subpopulation. Finally, the appropriate program
trees are added as new terminal nodes to the terminal
set, resulting in a new hierarchy. The best-fitting
program trees from each subpopulation with high
synergistic value are chosen as basis functions. The
proposed approach uses a linear function of the basis
functions to solve the regression problem. The proposed
method is evaluated on several real-world benchmark
datasets. The datasets are divided into four classes:
small-difficult, small-easy, large-difficult, and
large-easy. The proposed method improves the results of
the best methods for the regression problem by
232percent and 62percent for small difficult data sets
and large difficult data sets, respectively",
- }
Genetic Programming entries for
Mohaddeseh Koosha
Ghazaleh Khodabandelou
Mohammad Mehdi Ebadzadeh
Citations