Inductive data mining: Automatic generation of decision trees from data for QSAR modelling and process historical data analysis
Created by W.Langdon from
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- @InCollection{Ma2008581,
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author = "Chao Y Ma and Frances V Buontempo and Xue Z Wang",
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title = "Inductive data mining: Automatic generation of
decision trees from data for QSAR modelling and process
historical data analysis",
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editor = "Bertrand Braunschweig and Xavier Joulia",
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booktitle = "18th European Symposium on Computer Aided Process
Engineering",
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publisher = "Elsevier",
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year = "2008",
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volume = "25",
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pages = "581--586",
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series = "Computer Aided Chemical Engineering",
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ISSN = "1570-7946",
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DOI = "doi:10.1016/S1570-7946(08)80102-2",
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URL = "http://www.sciencedirect.com/science/article/B8G5G-4TK2DGX-3M/2/2d0cbf83807000db928a8f08986360cf",
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keywords = "genetic algorithms, genetic programming, inductive
data mining, decision trees, QSAR, process historical
data analysis",
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abstract = "A new inductive data mining method for automatic
generation of decision trees from data (GPTree) is
presented. Compared with other decision tree induction
techniques that are based upon recursive partitioning
employing greedy searches to choose the best splitting
attribute and value at each node therefore will
necessarily miss regions of the search space, GPTree
can overcome the problem. In addition, the approach is
extended to a new method (YAdapt) that models the
original continuous endpoint by adaptively finding
suitable ranges to describe the endpoints during the
tree induction process, removing the need for
discretization prior to tree induction and allowing the
ordinal nature of the endpoint to be taken into account
in the models built. A strategy for further improving
the predictive performance for previously unseen data
is investigated that uses multiple decisions trees,
i.e., a decision forest, and a majority voting strategy
to give a prediction (GPForest). The methods were
applied to QSAR (quantitative structure--activity
relationships) modeling for eco-toxicity prediction of
chemicals and to the analysis of a historical database
for a wastewater treatment plant.",
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notes = "See \cite{Ma20091602}",
- }
Genetic Programming entries for
Cai-Yun Ma
Frances V Buontempo
Xue Zhong Wang
Citations