@inproceedings{64011efe9d1c4826af43de31320d4045,
title = "Space decomposition in data mining - A clustering approach",
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.",
keywords = "Data mining, Induction generators, Probability distribution, Euclidean distance, very large databases, pattern clustering, database theory",
author = "Oded Maimon and Lior Rokach and Inbal Lavi",
year = "2002",
month = jan,
day = "1",
doi = "10.1109/EEEI.2002.1178345",
language = "English",
series = "IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "101--104",
booktitle = "22nd Convention of Electrical and Electronics Engineers in Israel, Proceedings",
address = "United States",
note = "22nd Convention of Electrical and Electronics Engineers in Israel ; Conference date: 01-12-2002",
}