{"title":"聚类位置和数据集大小对两阶段k-means算法的影响","authors":"R. Salman, V. Kecman","doi":"10.1109/IWECMS.2011.5952377","DOIUrl":null,"url":null,"abstract":"Paper introduces the 2-stage k-means algorithm which is faster than the standard 1-stage k-means algorithm. The main idea of the 2-stages is to move, in the first stage (fast), the centers of the clusters closer to their final locations. This will be done by using a small part of the data to achieve faster calculation. The next stage (slow) stage will start from the centers found during the first stage (fast). Different initial locations of the clusters have been used while testing the algorithms here. With bigger datasets, it is shown that the 2-stage clustering method achieves better speed-up.","PeriodicalId":211450,"journal":{"name":"2011 10th International Workshop on Electronics, Control, Measurement and Signals","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The effect of cluster location and dataset size on 2-stage k-means algorithm\",\"authors\":\"R. Salman, V. Kecman\",\"doi\":\"10.1109/IWECMS.2011.5952377\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Paper introduces the 2-stage k-means algorithm which is faster than the standard 1-stage k-means algorithm. The main idea of the 2-stages is to move, in the first stage (fast), the centers of the clusters closer to their final locations. This will be done by using a small part of the data to achieve faster calculation. The next stage (slow) stage will start from the centers found during the first stage (fast). Different initial locations of the clusters have been used while testing the algorithms here. With bigger datasets, it is shown that the 2-stage clustering method achieves better speed-up.\",\"PeriodicalId\":211450,\"journal\":{\"name\":\"2011 10th International Workshop on Electronics, Control, Measurement and Signals\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 10th International Workshop on Electronics, Control, Measurement and Signals\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWECMS.2011.5952377\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 10th International Workshop on Electronics, Control, Measurement and Signals","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWECMS.2011.5952377","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The effect of cluster location and dataset size on 2-stage k-means algorithm
Paper introduces the 2-stage k-means algorithm which is faster than the standard 1-stage k-means algorithm. The main idea of the 2-stages is to move, in the first stage (fast), the centers of the clusters closer to their final locations. This will be done by using a small part of the data to achieve faster calculation. The next stage (slow) stage will start from the centers found during the first stage (fast). Different initial locations of the clusters have been used while testing the algorithms here. With bigger datasets, it is shown that the 2-stage clustering method achieves better speed-up.