Control point selection for dimensionality reduction by radial basis function
<p>This research deals with dimensionality reduction technique which is based on radial basis function (RBF) theory. The technique uses RBF for mapping multidimensional data points into a low-dimensional space by interpolating the previously calculated position of so-called control points. Thi...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Klaipėda University
2016-02-01
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| Series: | Computational Science and Techniques |
| Online Access: | http://journals.ku.lt/index.php/CST/article/view/1095 |
| _version_ | 1819154099610845184 |
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| author | Kotryna Paulauskienė Olga Kurasova |
| author_facet | Kotryna Paulauskienė Olga Kurasova |
| author_sort | Kotryna Paulauskienė |
| collection | DOAJ |
| description | <p>This research deals with dimensionality reduction technique which is based on radial basis function (RBF) theory. The technique uses RBF for mapping multidimensional data points into a low-dimensional space by interpolating the previously calculated position of so-called control points. This paper analyses various ways of selection of control points (<em>regularized</em> <em>orthogonal least squares</em> method, <em>random</em> and <em>stratified</em> selections). The experiments have been carried out with 8 real and artificial data sets. Positions of the control points in a low-dimensional space are found by principal component analysis. We demonstrate that <em>random</em> and <em>stratified</em> selections of control points are efficient and acceptable in terms of balance between projection error (<em>stress</em>) and time-consumption.</p><p>DOI: 10.15181/csat.v4i1.1095</p> |
| first_indexed | 2024-12-22T15:15:42Z |
| format | Article |
| id | doaj.art-3e6cbe44d83c43fc88435207c0105293 |
| institution | Directory Open Access Journal |
| issn | 2029-9966 |
| language | English |
| last_indexed | 2024-12-22T15:15:42Z |
| publishDate | 2016-02-01 |
| publisher | Klaipėda University |
| record_format | Article |
| series | Computational Science and Techniques |
| spelling | doaj.art-3e6cbe44d83c43fc88435207c01052932022-12-21T18:21:45ZengKlaipėda UniversityComputational Science and Techniques2029-99662016-02-014148749910.15181/csat.v4i1.10951105Control point selection for dimensionality reduction by radial basis functionKotryna Paulauskienė0Olga Kurasova1Vilnius University,Institute of Mathematics and InformaticsVilnius University, Institute of Mathematics and Informatics<p>This research deals with dimensionality reduction technique which is based on radial basis function (RBF) theory. The technique uses RBF for mapping multidimensional data points into a low-dimensional space by interpolating the previously calculated position of so-called control points. This paper analyses various ways of selection of control points (<em>regularized</em> <em>orthogonal least squares</em> method, <em>random</em> and <em>stratified</em> selections). The experiments have been carried out with 8 real and artificial data sets. Positions of the control points in a low-dimensional space are found by principal component analysis. We demonstrate that <em>random</em> and <em>stratified</em> selections of control points are efficient and acceptable in terms of balance between projection error (<em>stress</em>) and time-consumption.</p><p>DOI: 10.15181/csat.v4i1.1095</p>http://journals.ku.lt/index.php/CST/article/view/1095 |
| spellingShingle | Kotryna Paulauskienė Olga Kurasova Control point selection for dimensionality reduction by radial basis function Computational Science and Techniques |
| title | Control point selection for dimensionality reduction by radial basis function |
| title_full | Control point selection for dimensionality reduction by radial basis function |
| title_fullStr | Control point selection for dimensionality reduction by radial basis function |
| title_full_unstemmed | Control point selection for dimensionality reduction by radial basis function |
| title_short | Control point selection for dimensionality reduction by radial basis function |
| title_sort | control point selection for dimensionality reduction by radial basis function |
| url | http://journals.ku.lt/index.php/CST/article/view/1095 |
| work_keys_str_mv | AT kotrynapaulauskiene controlpointselectionfordimensionalityreductionbyradialbasisfunction AT olgakurasova controlpointselectionfordimensionalityreductionbyradialbasisfunction |