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Types of error in QSAR/QSPR development and use. --------------------------------------------------------- 1 Failure to take account of data heterogeneity 2 Use of inappropriate endpoint data 3 Use of collinear descriptors 4 Use of incomprehensible descriptors 5 Error in descriptor values 6 Poor transferability of QSAR/QSPR 7 Inadequate/undefined applicability domain 8 Unacknowledged omission of data points 9 Use of inadequate data 10 Replication of compounds in dataset 11 Too narrow a range of endpoint values 12 Over-fitting of data 13 Use of excessive numbers of descriptors in a QSAR/QSPR 14 Lack of/inadequate statistics 15 Incorrect calculation 16 Lack of descriptor auto-scaling 17 Misuse/misinterpretation of statistics 18 No consideration of distribution of residuals 19 Inadequate training/test set selection 20 Failure to validate a QSAR/QSPR correctly 21 Lack of mechanistic interpretation ¸ü¶àÄÚÈÝ£¬¿´¸½¼þ¡£ [ Last edited by lei0736 on 2009-11-24 at 20:57 ] |
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