Finding spatio-temporal patterns in climate data using clustering
This paper presents a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data non-linearly separable in input space. This work gets inspiration from the notion that a non-linear data transfo...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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2005
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| Online Access: | http://eprints.utm.my/7574/1/Sap_M_N_Md_2005_Finding_Spatio-Temporal_Patterns_Climate.pdf |
| _version_ | 1796854237195403264 |
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| author | Md. Sap, Mohd. Noor Awan, A. Majid |
| author_facet | Md. Sap, Mohd. Noor Awan, A. Majid |
| author_sort | Md. Sap, Mohd. Noor |
| collection | ePrints |
| description | This paper presents a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data non-linearly separable in input space. This work gets inspiration from the notion that a non-linear data transformation into some high dimensional feature space increases the possibility of linear separability of the patterns in the transformed space. Therefore, it simplifies exploration of the associated structure in the data. Kernel methods implicitly perform a non-linear mapping of the input data into a high dimensional feature space by replacing the inner products with an appropriate positive definite function. In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data. |
| first_indexed | 2024-03-05T18:11:24Z |
| format | Conference or Workshop Item |
| id | utm.eprints-7574 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T18:11:24Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | utm.eprints-75742017-08-30T04:53:57Z http://eprints.utm.my/7574/ Finding spatio-temporal patterns in climate data using clustering Md. Sap, Mohd. Noor Awan, A. Majid QA75 Electronic computers. Computer science This paper presents a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data non-linearly separable in input space. This work gets inspiration from the notion that a non-linear data transformation into some high dimensional feature space increases the possibility of linear separability of the patterns in the transformed space. Therefore, it simplifies exploration of the associated structure in the data. Kernel methods implicitly perform a non-linear mapping of the input data into a high dimensional feature space by replacing the inner products with an appropriate positive definite function. In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data. 2005 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/7574/1/Sap_M_N_Md_2005_Finding_Spatio-Temporal_Patterns_Climate.pdf Md. Sap, Mohd. Noor and Awan, A. Majid (2005) Finding spatio-temporal patterns in climate data using clustering. In: Proceedings - 2005 International Conference on Cyberworlds, CW 2005, 23th -25th Nov. 2005. http://dx.doi.org/10.1109/CW.2005.45 |
| spellingShingle | QA75 Electronic computers. Computer science Md. Sap, Mohd. Noor Awan, A. Majid Finding spatio-temporal patterns in climate data using clustering |
| title | Finding spatio-temporal patterns in climate data using clustering |
| title_full | Finding spatio-temporal patterns in climate data using clustering |
| title_fullStr | Finding spatio-temporal patterns in climate data using clustering |
| title_full_unstemmed | Finding spatio-temporal patterns in climate data using clustering |
| title_short | Finding spatio-temporal patterns in climate data using clustering |
| title_sort | finding spatio temporal patterns in climate data using clustering |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/7574/1/Sap_M_N_Md_2005_Finding_Spatio-Temporal_Patterns_Climate.pdf |
| work_keys_str_mv | AT mdsapmohdnoor findingspatiotemporalpatternsinclimatedatausingclustering AT awanamajid findingspatiotemporalpatternsinclimatedatausingclustering |