A Fast Logdet Divergence Based Metric Learning Algorithm for Large Data Sets Classification
Large data sets classification is widely used in many industrial applications. It is a challenging task to classify large data sets efficiently, accurately, and robustly, as large data sets always contain numerous instances with high dimensional feature space. In order to deal with this problem, in...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2014/463981 |
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| author | Jiangyuan Mei Jian Hou Jicheng Chen Hamid Reza Karimi |
| author_facet | Jiangyuan Mei Jian Hou Jicheng Chen Hamid Reza Karimi |
| author_sort | Jiangyuan Mei |
| collection | DOAJ |
| description | Large data sets classification is widely used in many industrial applications. It is a challenging task to classify
large data sets efficiently, accurately, and robustly, as large data sets always contain numerous instances with high
dimensional feature space. In order to deal with this problem, in this paper we present an online Logdet divergence
based metric learning (LDML) model by making use of the powerfulness of metric learning. We firstly generate
a Mahalanobis matrix via learning the training data with LDML model. Meanwhile, we propose a compressed
representation for high dimensional Mahalanobis matrix to reduce the computation complexity in each iteration.
The final Mahalanobis matrix obtained this way measures the distances between instances accurately and serves as
the basis of classifiers, for example, the k-nearest neighbors classifier. Experiments on benchmark data sets demonstrate that the proposed algorithm compares favorably with the state-of-the-art methods. |
| format | Article |
| id | doaj-art-4ff22fe209ef43478254efd83141efb6 |
| institution | OA Journals |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-4ff22fe209ef43478254efd83141efb62025-08-20T02:05:38ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/463981463981A Fast Logdet Divergence Based Metric Learning Algorithm for Large Data Sets ClassificationJiangyuan Mei0Jian Hou1Jicheng Chen2Hamid Reza Karimi3Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150080, ChinaSchool of Information Science and Technology, Bohai University, No. 19, Keji Road, Jinzhou 121013, ChinaResearch Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150080, ChinaDepartment of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, NorwayLarge data sets classification is widely used in many industrial applications. It is a challenging task to classify large data sets efficiently, accurately, and robustly, as large data sets always contain numerous instances with high dimensional feature space. In order to deal with this problem, in this paper we present an online Logdet divergence based metric learning (LDML) model by making use of the powerfulness of metric learning. We firstly generate a Mahalanobis matrix via learning the training data with LDML model. Meanwhile, we propose a compressed representation for high dimensional Mahalanobis matrix to reduce the computation complexity in each iteration. The final Mahalanobis matrix obtained this way measures the distances between instances accurately and serves as the basis of classifiers, for example, the k-nearest neighbors classifier. Experiments on benchmark data sets demonstrate that the proposed algorithm compares favorably with the state-of-the-art methods.http://dx.doi.org/10.1155/2014/463981 |
| spellingShingle | Jiangyuan Mei Jian Hou Jicheng Chen Hamid Reza Karimi A Fast Logdet Divergence Based Metric Learning Algorithm for Large Data Sets Classification Abstract and Applied Analysis |
| title | A Fast Logdet Divergence Based Metric Learning Algorithm for Large Data Sets Classification |
| title_full | A Fast Logdet Divergence Based Metric Learning Algorithm for Large Data Sets Classification |
| title_fullStr | A Fast Logdet Divergence Based Metric Learning Algorithm for Large Data Sets Classification |
| title_full_unstemmed | A Fast Logdet Divergence Based Metric Learning Algorithm for Large Data Sets Classification |
| title_short | A Fast Logdet Divergence Based Metric Learning Algorithm for Large Data Sets Classification |
| title_sort | fast logdet divergence based metric learning algorithm for large data sets classification |
| url | http://dx.doi.org/10.1155/2014/463981 |
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