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Decision‐tree construction and analysis
Author(s) -
Murphy Patrick,
Olson Betty H.
Publication year - 1996
Publication title -
journal ‐ american water works association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.466
H-Index - 74
eISSN - 1551-8833
pISSN - 0003-150X
DOI - 10.1002/j.1551-8833.1996.tb06502.x
Subject(s) - decision tree , reliability (semiconductor) , decision tree model , tree (set theory) , sulfate reducing bacteria , decision analysis , sulfate , computer science , environmental science , data mining , statistics , mathematics , chemistry , mathematical analysis , power (physics) , physics , organic chemistry , quantum mechanics
Decision‐tree theory may be useful in understanding complex biological systems. Decision‐tree construction and analysis indicate the quantitative occurrence of sulfate‐reducing bacteria in a groundwater basin. The decision‐tree analysis allowed determination of the most important measured variables (discriminators) associated with the occurrence of sulfate‐reducing bacteria. Those variables may be used to improve reliability and validity of the tree. Statistical validation of endpoint data (leaves) is described, and decision trees are presented that increase the understanding of individual wells and hypothesize causes for sulfate‐reducing bacteria.