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The Support Vector Machine algorithm is sensitive to the choice of parameter settings. If these are not set correctly, the algorithm may have a substandard performance. Suggesting a good setting is thus an important problem. We propose a meta-learning methodology for this purpose and exploit information about the past performance of different settings. The(More)
This report deals with spatial data structures for indexing and with their usability for knowledge discovery in spatial data. Huge amount of data processed in spatial data mining (or in data mining generally) requires using some indexing structures to speed up the mining process. Typical data types and operations used in geographic information systems are(More)
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