An improved binary differential search (improved BDS) algorithm is proposed for QSAR classification of diverse series of antimicrobial compounds against Candida albicans inhibitors. The transfer functions is the most important component of the BDS algorithm, and converts continuous values of the donor into discrete values. In this paper, the eight types of transfer functions are investigated to verify their efficiency in improving BDS algorithm performance in QSAR classification. The performance was evaluated using three metrics: classification accuracy (CA), geometric mean of sensitivity and specificity (G-mean), and area under the curve. The Kruskal–Wallis test was also applied to show the statistical differences between the functions. Two functions, S1 and V4, show the best classification achievement, with a slightly better performance of V4 than S1. The V4 function takes the lowest iterations and selects the fewest descriptors. In addition, the V4 function yields the best CA and G-mean of 98.07% and 0.977%, respectively. The results prove that the V4 transfer function significantly improves the performance of the original BDS.

提出了一种改进的二进制差分搜索（改进的BDS）算法，用于对白色念珠菌的不同系列抗菌化合物进行QSAR分类抑制剂。传递函数是BDS算法的最重要组成部分，它将供体的连续值转换为离散值。本文研究了八种类型的传递函数，以验证它们在提高QSAR分类中BDS算法性能方面的效率。使用三个指标评估性能：分类准确性（CA），敏感性和特异性的几何平均值（G均值）以及曲线下面积。还使用Kruskal–Wallis检验来显示功能之间的统计差异。S1和V4这两个函数显示出最佳的分类效果，V4的性能比S1略好。V4函数的迭代次数最少，选择的描述符最少。此外，V4功能可产生最佳的CA和G均值分别为98.07％和0.977％。结果证明，V4传递函数显着提高了原始BDS的性能。