A comparative evaluation approach for the classification of rotifers with modified non-parametric kNN

Through a process of comparative evaluation, several of the modified algorithms proposed-comprising both individual and hybrid models-were found to perform better overall than the classical kNN method. Refinements related to class-size weighting, in particular, were shown to heighten the accuracy of the classical kNN model considerably. Close evaluation of the various models created revealed kNN-CCS and F-kNN-CCS, in their application to the edited data sets, to be the most reliable individual modified and hybrid models respectively, with levels of accuracy greater than 95%.