.png){kind=icon}
Return
Learning classification rules from an ion chromatography database using a genetic based classifier system
.png){kind=icon}
PRE
AI
DOI：10.1016/S0003-2670(96)00629-0.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
A classifier system based on genetic algorithm methodology was developed for the automatic extraction of production rules from a database of about 6000 ion chromatography (IC) method examples. This machine learning strategy generated heuristics that can assist in the choice for a detection method for a specified set of IC method and solute properties. It was shown that the final set of rules proposed detectors that agreed with the database for 76% of the cases. Application to a separate test set showed a prediction ability of 82%. The database, because of the characteristics of the included cases, did not allow for a significant improvement of these results. However, the results are of significance for the further development of knowledge systems, which assist in the design of IC methods. Furthermore, this dataset comprised a considerable challenge to the applied machine learning method.
Keywords:
ion chromatography
genetic algorithm
classification
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6
Papers:
3.3W
Citations:
6.1W
Organization
No organization information available
Cited Papers
.png){kind=icon}
ShareSave
ShareSaveShareSaveShareSaveShareSave
View more