The ISIDA_NB program is an implementation of consensus naive Bayesian classifier into the ISIDA_QSPR program. Ensemble modeling workflow of the ISIDA_NB program includes (i) generation of ensemble of individual classification models, (ii) selection of the most predictive ones using internal and external cross-validations and (iii) consensus application of selected models to a test set compounds.

Ensembles of individual models are generated by varying parameters of naive Bayesian model (weight of Laplace correction, score threshold), variable selection techniques (variable filtering, excluding concatenated fragments) and using of multiple types of molecular fragments as descriptors. The program runs under the Windows operating system. The graphical interface pilots this workflow and supports the analysis of the obtained results. The Consensus Predictor tool realizes property predictions and virtual screening using previously obtained consensus models.