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A review of support vector machines with respect to spatial data
Published 2007Conference or Workshop Item -
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Clustering Spatial Data Using a Kernel-Based Algorithm
Published 2005“…Firstly, in this paper, selective kernel-based clustering techniques are analyzed and their shortcomings are identified especially for spatial data analysis. Finally, we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering spatial data as a case study. …”
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Conference or Workshop Item -
3
An intelligent system based on kernel methods for crop yield prediction
Published 2006“…The algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield. …”
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Conference or Workshop Item -
4
Finding spatio-temporal patterns in climate data using clustering
Published 2005“…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.…”
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Conference or Workshop Item -
5
A framework for predicting oil-palm yield from climate data
Published 2006“…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, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.…”
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Conference or Workshop Item -
6
Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.
Published 2005“…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, and thus can be used for predicting oil-palm yield by analyzing various factors affecting oil-palm yield.…”
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