Space decomposition in data mining-a clustering approach

Space decomposition in data mining-a clustering approach. Maimon, O., Rokach, L., & Lavi, I. In Electrical and Electronics Engineers in Israel, 2002. The 22nd Convention of, pages 101–104, 2002. IEEE.

Link doi abstract bibtex

Decomposition may divide the database horizontally (subsets of rows or tuples) or vertically. It may be aimed at minimizing space and time needed for the classification of a dataset (e.g. sampling, windowing) or rather attempt to improve accuracy (e.g. bagging, boosting). This paper presents a horizontal space-decomposition algorithm, exploiting the K-means clustering algorithm. It is aimed at decreasing error rate compared to the simple classifier embedded in it while being rather understandable.

@inproceedings{maimon2002space,
  author        = {Maimon, O. and Rokach, L. and Lavi, I.},
  organization  = {IEEE},
  title         = {Space decomposition in data mining-a clustering approach},
  pages         = {101--104},
  year          = {2002},
  booktitle     = {Electrical and Electronics Engineers in Israel, 2002. The 22nd Convention of},
  abstract={ Decomposition may divide the database horizontally (subsets of rows or tuples) or vertically. It may be aimed at minimizing space and time needed for the classification of a dataset (e.g. sampling, windowing) or rather attempt to improve accuracy (e.g. bagging, boosting). This paper presents a horizontal space-decomposition algorithm, exploiting the K-means clustering algorithm. It is aimed at decreasing error rate compared to the simple classifier embedded in it while being rather understandable.},
  doi={10.1109/EEEI.2002.1178345}, 
  ee		= {http://dx.doi.org/10.1109/EEEI.2002.1178345},
  keywords	= {Ensemble learning, Decomposition, Clustering}
}

Downloads: 0

{"_id":{"_str":"5342b7670e946d920a0033df"},"__v":19,"authorIDs":["5463d9f24f4818cf4f00041a","5de9bbce5b51bcde01000139","T7nhCxakPutsxwxZG"],"author_short":["Maimon, O.","Rokach, L.","Lavi, I."],"bibbaseid":"maimon-rokach-lavi-spacedecompositionindataminingaclusteringapproach-2002","bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"propositions":[],"lastnames":["Maimon"],"firstnames":["O."],"suffixes":[]},{"propositions":[],"lastnames":["Rokach"],"firstnames":["L."],"suffixes":[]},{"propositions":[],"lastnames":["Lavi"],"firstnames":["I."],"suffixes":[]}],"organization":"IEEE","title":"Space decomposition in data mining-a clustering approach","pages":"101–104","year":"2002","booktitle":"Electrical and Electronics Engineers in Israel, 2002. The 22nd Convention of","abstract":"Decomposition may divide the database horizontally (subsets of rows or tuples) or vertically. It may be aimed at minimizing space and time needed for the classification of a dataset (e.g. sampling, windowing) or rather attempt to improve accuracy (e.g. bagging, boosting). This paper presents a horizontal space-decomposition algorithm, exploiting the K-means clustering algorithm. It is aimed at decreasing error rate compared to the simple classifier embedded in it while being rather understandable.","doi":"10.1109/EEEI.2002.1178345","ee":"http://dx.doi.org/10.1109/EEEI.2002.1178345","keywords":"Ensemble learning, Decomposition, Clustering","bibtex":"@inproceedings{maimon2002space,\r\n author = {Maimon, O. and Rokach, L. and Lavi, I.},\r\n organization = {IEEE},\r\n title = {Space decomposition in data mining-a clustering approach},\r\n pages = {101--104},\r\n year = {2002},\r\n booktitle = {Electrical and Electronics Engineers in Israel, 2002. The 22nd Convention of},\r\n abstract={ Decomposition may divide the database horizontally (subsets of rows or tuples) or vertically. It may be aimed at minimizing space and time needed for the classification of a dataset (e.g. sampling, windowing) or rather attempt to improve accuracy (e.g. bagging, boosting). This paper presents a horizontal space-decomposition algorithm, exploiting the K-means clustering algorithm. It is aimed at decreasing error rate compared to the simple classifier embedded in it while being rather understandable.},\r\n doi={10.1109/EEEI.2002.1178345}, \r\n ee\t\t= {http://dx.doi.org/10.1109/EEEI.2002.1178345},\r\n keywords\t= {Ensemble learning, Decomposition, Clustering}\r\n}\r\n\r\n","author_short":["Maimon, O.","Rokach, L.","Lavi, I."],"key":"maimon2002space","id":"maimon2002space","bibbaseid":"maimon-rokach-lavi-spacedecompositionindataminingaclusteringapproach-2002","role":"author","urls":{"Link":"http://dx.doi.org/10.1109/EEEI.2002.1178345"},"keyword":["Ensemble learning","Decomposition","Clustering"],"metadata":{"authorlinks":{}},"downloads":0,"html":""},"bibtype":"inproceedings","biburl":"www.ise.bgu.ac.il/faculty/liorr/liorrokach122012.txt","downloads":0,"keywords":["ensemble learning","decomposition","clustering"],"search_terms":["space","decomposition","data","mining","clustering","approach","maimon","rokach","lavi"],"title":"Space decomposition in data mining-a clustering approach","year":2002,"dataSources":["HLsp6sSsQQZwywcSL","NhJvHJs9CpZ5T5D7K"]}