Evaluation of model predictive ability by external validation techniques

By Viviana Consonni, Davide Ballabio, Roberto Todeschini. 2010

351 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/8298f5ed89c3a075747def32c6c9c33f33a366c3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Kamel Mansouri
2. Richard S. Judson
3. Christopher M. Grulke
4. Antony J. Williams
5. Viviana Consonni
6. Roberto Todeschini
7. Davide Ballabio
8. Paola Gramatica

In Management Science and Operations Research

1. Kamel Mansouri

In Statistics and Probability

1. Kamel Mansouri
2. Richard S. Judson
3. Viviana Consonni
4. Roberto Todeschini
5. Davide Ballabio

Citations in the corpus

• Comparison of Different Approaches to Define the Applicability Domain of QSAR Models (2012, methodology): “The results were tabulated informing the model’s statistics for each AD approach on the compounds considered inside the applicability domain using the following parameters: i) Number of test compounds considered outside the domain of applicability; ii) Predictive squared correlation coefficient Q(2)”
• OPERA models for predicting physicochemical properties and environmental fate endpoints (2018, methodology): “Goodness-of-fit, robustness, and predictivity were evaluated using internal fivefold cross-validation (CV) and external test set techniques [51, 61, 62].”