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Internal Test Sets (ITS) Method: a new cross-validation technique to assess the predictive capability of QSAR models. Application to a benchmark set of steroids

A new internal cross-validation method is presented for assessing the true predictive capability of QSAR models. The test is general and can be applied in many QSAR/QSPR approaches. In this work, the method is tested on a well-known benchmark set of steroids. In order to make the calculations, Topological Quantum Similarity Indices and Multiple Linear Regression models were considered

Sociedad Chilena de Química

Author: Besalú i Llorà, Emili
Vera, Leonel
Abstract: A new internal cross-validation method is presented for assessing the true predictive capability of QSAR models. The test is general and can be applied in many QSAR/QSPR approaches. In this work, the method is tested on a well-known benchmark set of steroids. In order to make the calculations, Topological Quantum Similarity Indices and Multiple Linear Regression models were considered
Document access: http://hdl.handle.net/2072/239928
Language: eng
Publisher: Sociedad Chilena de Química
Rights: Attribution-NonCommercial 3.0 Spain
Rights URI: http://creativecommons.org/licenses/by-nc/3.0/es/
Subject: Química quàntica
Quantum chemistry
QSAR (Bioquímica)
QSAR (Biochemistry)
Title: Internal Test Sets (ITS) Method: a new cross-validation technique to assess the predictive capability of QSAR models. Application to a benchmark set of steroids
Type: info:eu-repo/semantics/article
Repository: Recercat

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