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Validation is the process by which the reliability and relevance of a procedure are established for a specific purpose. However, it is now being accepted that validation is a more holistic process that includes assessment of issues such as data quality, applicability of the model, and mechanistic interpretability in addition to statistical assessment. The validation strategies check the reliability of the developed models for their possible application on a new set of data, and confidence of prediction can thus be judged. In the QSAR community, the validation of a model is little more than an assessment of statistical fit, and occasionally predictivity using cross-validation techniques Validation is a crucial aspect of any quantitative structure¿activity relationship (QSAR) modeling. This book provides a brief overview about various techniques of validation used in QSAR modeling.
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