|
|
|
 |
|
 |
|
Summary Grids: Building Accurate Multidimensional Histograms
|
Pedro Furtado and
H. Madeira
View Paper (PDF)
Return to Session 4A: Data Analysis and Mining
Data summarization is very important for many data
analysis tasks. In this paper we propose a simple but efficient data
summarization algorithm, which outputs a histogram for multidimensional data,
and make a comparative study of its usage with different distributions and with
existing algorithms. The idea is to iteratively grow and modify regions of
homogeneous data. This is a different strategy from a commonly used strategy of
iteratively fracturing subspaces using straight lines. This work compares both
strategies and concludes that the new technique is better and helds good
results. We also concluded that discriminate handling of outliers is important
to provide good approximates.
Copyright(C) 2000 ACM
|
|
|
|
|
|
|
