Journal ArticleDOI
Further exploring rm2 metrics for validation of QSPR models
TLDR
In this article, some additional variants of r m 2 metrics have been proposed and their applications in judging the quality of predictions of QSPR models have been shown by analyzing results of the QSPr models obtained from three different data sets (n = 119, 90, and 384).About:
This article is published in Chemometrics and Intelligent Laboratory Systems.The article was published on 2011-05-01. It has received 467 citations till now. The article focuses on the topics: Test set.read more
Citations
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Journal ArticleDOI
Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient.
Nicola Chirico,Paola Gramatica +1 more
TL;DR: The concordance correlation coefficient is proposed as a complementary, or alternative, more prudent measure of a QSAR model to be externally predictive, and works well on real data sets, where it seems to be more stable, and helps in making decisions when the validation measures are in conflict.
Journal ArticleDOI
QSARINS: A new software for the development, analysis, and validation of QSAR MLR models
TL;DR: The Insubria Persistent Bioaccumulative and Toxic (PBT) Index model for the prediction of the cumulative behavior of new chemicals as PBTs is implemented and the user can validate single models, predeveloped using also different software.
Journal ArticleDOI
Real external predictivity of QSAR models. Part 2. New intercomparable thresholds for different validation criteria and the need for scatter plot inspection.
Nicola Chirico,Paola Gramatica +1 more
TL;DR: This work has studied and compared the general trends of the various criteria relative to different possible biases in external data distributions, using a wide range of different simulated scenarios and proposed new thresholds for each criterion in defining a QSAR model as really externally predictive in a more precautionary approach.
Journal ArticleDOI
Comparative Studies on Some Metrics for External Validation of QSPR Models
TL;DR: This report questions the appropriateness of the common practice of the "classic" approach of external validation based on a single test set and derives a conclusion about predictive quality of a model on the basis of a particular validation metric.
Journal ArticleDOI
Some case studies on application of "r(m)2" metrics for judging quality of quantitative structure-activity relationship predictions: emphasis on scaling of response data.
TL;DR: The present study reports that the web application can be easily used for computation of rm2 metrics provided observed and QSAR‐predicted data for a set of compounds are available and scaling of response data is recommended prior to rm2 calculation.
References
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Journal ArticleDOI
Beware of q2
TL;DR: It is argued that the high value of LOO q2 appears to be the necessary but not the sufficient condition for the model to have a high predictive power, which is the general property of QSAR models developed using LOO cross-validation.
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Principles of QSAR models validation: internal and external
TL;DR: Evidence is presented that only models that have been validated externally, after their internal validation, can be considered reliable and applicable for both external prediction and regulatory purposes.
Journal ArticleDOI
Best Practices for QSAR Model Development, Validation, and Exploitation.
TL;DR: Most critical QSAR modeling routines that are regarded as best practices in the field are examined, including procedures used to validate models, both internally and externally, as well as the need to define model applicability domains that should be used when models are employed for the prediction of external compounds or compound libraries.
Journal ArticleDOI
Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs.
Lennart Eriksson,Joanna Jaworska,Andrew Worth,Mark T. D. Cronin,Robert M McDowell,Paola Gramatica +5 more
TL;DR: This article provides an overview of methods for reliability assessment of quantitative structure-activity relationship (QSAR) models in the context of regulatory acceptance of human health and environmental QSARs.
Journal ArticleDOI
Application of Genetic Function Approximation to Quantitative Structure-Activity Relationships and Quantitative Structure-Property Relationships
David Rogers,Anton J. Hopfinger +1 more
TL;DR: The genetic function approximation (GFA) algorithm is applied to three published data sets to demonstrate it is an effective tool for doing both QSAR and QSPR.
Related Papers (5)
Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient.
Nicola Chirico,Paola Gramatica +1 more