Applicability domain for classification problems

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چکیده

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Applicability domain for classification problems

Classification models are frequent in QSAR modeling. It is of crucial importance to provide good accuracy estimation for classification. Applicability domain provides additional information to identify which compounds are classified with best accuracy and which are expected to have poor and unreliable predictions. The selection of the most reliable predictions can dramatically improve performan...

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The estimation of accuracy and applicability of QSAR and QSPR models for biological and physicochemical properties represents a critical problem. The developed parameter of "distance to model" (DM) is defined as a metric of similarity between the training and test set compounds that have been subjected to QSAR/QSPR modeling. In our previous work, we demonstrated the utility and optimal performa...

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ژورنال

عنوان ژورنال: Journal of Cheminformatics

سال: 2010

ISSN: 1758-2946

DOI: 10.1186/1758-2946-2-s1-p41