Decision tree method for the classification of chemical pollutants: Incorporation of across-chemical variability and within-chemical uncertainty
- Univ. of California, Berkeley, CA (United States). School of Public Health
- Lawrence Berkeley National Lab., CA (United States)
The authors have developed a decision tree methodology for the classification of chemicals by estimates of potential human exposure. The steps involved in the construction of a decision tree area as follows. Monte Carlo simulations are conducted by randomly sampling chemical and environmental properties, whose range of values represents the variability of parameters across a defined set of chemicals and environmental conditions. The tree structure is then defined by a series of constraints placed on the various chemical and environmental properties using the Classification and Regression Tree Algorithm (CART). Each node of the tree is associated with a human exposure value and is considered a bin, which classifies chemicals whose properties are consistent with those parametric constraints associated with the particular node. In addition to being associated with parametric constraints, each bin or tree node is associated with a human exposure level. In this manner, the tree structure functions as a template from which a set of chemicals are classified into parametric regions that are associated with an exposure level. To illustrate these properties, a case study was conducted in which exposures were estimated using the multimedia exposure model CalTOX assuming a regional chemical release into soil. A decision tree template was constructed and then used to classify 79 chemicals.
- OSTI ID:
- 323758
- Journal Information:
- Environmental Science and Technology, Journal Name: Environmental Science and Technology Journal Issue: 21 Vol. 32; ISSN ESTHAG; ISSN 0013-936X
- Country of Publication:
- United States
- Language:
- English
Similar Records
Lazy decision trees
CalTOX (registered trademark), A multimedia total exposure model spreadsheet user's guide. Version 4.0(Beta)