(untitled) (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Data normalization is one of the pre-processing approaches where the data is either scaled or transformed to make an equal contribution of each feature. The success of classification algorithms depends upon the quality of the data to obtain a generalized predictive model of the classification problem. The importance of data normalization for improving data quality. Therefore, this study aims to investigate the impact of z-score normalization method on accuracy of classification of liver diaseas. In this paper we apply z-score normalization on three classification algorithm Artificial Neural Network, Support Vector Machine, and K-nearest neighbour with two liver datasets. It has been observed from the results classification algorithms effected with z-score normalization.