Subspace Memory Clustering

• Authors: Łukasz Struski , Przemysław Spurek , Jacek Tabor
• Languages of publication: PL

Abstracts

PL

We present a new subspace clustering method called SuMC (Subspace Memory Clustering), which allows to efficiently divide a dataset D RN into k 2 N pairwise disjoint clusters of possibly different dimensions. Since our approach is based on the memory compression, we do not need to explicitly specify dimensions of groups: in fact we only need to specify the mean number of scalars which is used to describe a data-point. In the case of one cluster our method reduces to a classical Karhunen-Loeve (PCA) transform. We test our method on some typical data from UCI repository and on data coming from real-life experiments.

Keywords

PL

subspace clustering, projection clustering, PCA

• Publisher: [unknown2]
• Journal: Schedae Informaticae
• Year: 2015
• Volume: 24

Dates

published

2015

online

06 - 07 - 2016

Contributors

author

Łukasz Struski

author

Przemysław Spurek

author

Jacek Tabor