@inproceedings{16144e832e9945be88f7f34e47fb564d,
title = "A novel K-means classification method with genetic algorithm",
abstract = "Data classification is an important part in data mining field. However, problems of high amount of calculation and low accuracy always existing in data classification attract interests of many researchers. This paper proposes a K-Means classification method with genetic algorithm applied to faster and more accurate classification. A data preprocessing approach based on sorted neighborhood method (SNM) is designed to clean the redundancy data effectively. The K-Means method is then utilized to classify the processed records. In order to improve the efficiency and accuracy, the genetic algorithm (GA) is applied into K-Means model to perform the dimension reduction. The results of simulations and experiments demonstrate that the proposed method has better properties in efficiency and accuracy than the competing methods.",
keywords = "Data classification, Data mining, Genetic algorithm, K-Means classification, Sorted neighborhood method",
author = "Xuesi Li and Kai Jiang and Hongbo Wang and Xuejun Zhu and Ruochong Shi and Haobin Shi",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 5th International Conference on Progress in Informatics and Computing, PIC 2017 ; Conference date: 15-12-2017 Through 17-12-2017",
year = "2017",
doi = "10.1109/PIC.2017.8359511",
language = "英语",
series = "Proceedings of 2017 International Conference on Progress in Informatics and Computing, PIC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "40--44",
booktitle = "Proceedings of 2017 International Conference on Progress in Informatics and Computing, PIC 2017",
}