A Simple Inter-Class Distance Parameter for Predictive SAR/QSAR Models
| Autor: | H. Gregg Claycamp, Nancy B. Sussman |
|---|---|
| Rok vydání: | 1999 |
| Předmět: |
Pharmacology
Quantitative structure–activity relationship business.industry Separation (statistics) Pattern recognition Machine learning computer.software_genre Class (biology) Measure (mathematics) Statistical classification Simple (abstract algebra) Artificial intelligence Sensitivity (control systems) business computer Selection (genetic algorithm) Mathematics |
| Zdroj: | Quantitive Structure-Activity Relationships. 18:11-15 |
| ISSN: | 1521-3838 0931-8771 |
| Popis: | The objective of many SAR or QSAR experiments is to develop statistical classification models that can separate chemicals into classes of “active” or “inactive” under a toxicological endpoint. Several existing statistical methods are often used to provide either quantitative or qualitative measures of the distance or separation between the active and inactive classes, including sensitivity, accuracy and the receiver-operator characteristic (ROC) curve. The present study proposes a simple “distance parameter” as a measure of the relative separation between classes of “active” and “inactive” chemicals. The distance parameter can be used alone or with existing statistical measures for both the optimization of a single model with respect to maximizing sensitivity and specificity, and also in the selection of the best model from among alternative models. |
| Databáze: | OpenAIRE |
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