K-nearest neighbors (KNN) algorithm is a non-parametric method used for the classification, which is based on the closest training instances in the feature space (Itskowitz and Tropsha, 2005). The number of nearest neighbors (K) and the weighting methods will affect the performance of KNN model. In this study, K (1, 3, 5, 7, 9, 11, 13, and 15) and two weighting schemes (uniform weight or distance-dependent weight) are explored during the cross-validation.