RRegrs: an R package for computer-aided model selection with multiple regression models

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• 作者：Georgia Tsiliki ; Cristian R. Munteanu ; Jose A. Seoane…
• 关键词：Multiple regression ; QSAR ; R package ; Caret ; based tool
• 刊名：Journal of Cheminformatics
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：7
• 期：1
• 全文大小：4,371 KB
• 刊物类别：Physics and Astronomy
• 刊物主题：Computer Applications in Chemistry
  Theoretical and Computational Chemistry
  Computational Biology/Bioinformatics
  Documentation and Information in Chemistry
  
• 出版者：Chemistry Central Ltd
• ISSN：1758-2946

文摘

Background Predictive regression models can be created with many different modelling approaches. Choices need to be made for data set splitting, cross-validation methods, specific regression parameters and best model criteria, as they all affect the accuracy and efficiency of the produced predictive models, and therefore, raising model reproducibility and comparison issues. Cheminformatics and bioinformatics are extensively using predictive modelling and exhibit a need for standardization of these methodologies in order to assist model selection and speed up the process of predictive model development. A tool accessible to all users, irrespectively of their statistical knowledge, would be valuable if it tests several simple and complex regression models and validation schemes, produce unified reports, and offer the option to be integrated into more extensive studies. Additionally, such methodology should be implemented as a free programming package, in order to be continuously adapted and redistributed by others.