y-Randomization and Its Variants in QSPR/QSAR
University of Basel · University of Freiburg
Abstract
Y-Randomization is a tool used in validation of QSPR/QSAR models, whereby the performance of the original model in data description (r2) is compared to that of models built for permuted (randomly shuffled) response, based on the original descriptor pool and the original model building procedure. We compared y-randomization and several variants thereof, using original response, permuted response, or random number pseudoresponse and original descriptors or random number pseudodescriptors, in the typical setting of multilinear regression (MLR) with descriptor selection. For each combination of number of observations (compounds), number of descriptors in the final model, and number of descriptors in the pool to…
Citation impact
- FWCI
- 14.58
- Percentile
- 100%
- References
- 44
Authors
3Topics & keywords
- Quantitative structure–activity relationship
- Selection (genetic algorithm)
- Multilinear map
- Mathematics
- Artificial intelligence
- Molecular descriptor
- Computer science
- Model selection