In fields such as atomic energy or materials, there is a lot of data set including data of different meaning and scale. If we do not consider scale and meaning, prediction errors could be done. In this paper, after normalizing variables, we applied K-nearest-neighbor method to materials dataset, and show that normalization lead to improvement of prediction.
