Support vector machine for large databases as classifier
RK Sevakula, NK Verma - … 2012, Bhubaneswar, India, December 20-22 …, 2012 - Springer
Swarm, Evolutionary, and Memetic Computing: Third International Conference …, 2012•Springer
Abstract Support Vector Machine (SVM) has been successful in multiple areas and is widely
accepted as the best off the shelf algorithm for classification. A standard SVM has O (n 3)
time and O (n 3) space complexities, hence making it limited in its usability for large
database. We know that in real world scenario, most of the databases where Data Mining is
used are large. This paper reviews various algorithms and techniques that have been
brought forth since 1995 by researchers for implementing SVMs in a practical manner for …
accepted as the best off the shelf algorithm for classification. A standard SVM has O (n 3)
time and O (n 3) space complexities, hence making it limited in its usability for large
database. We know that in real world scenario, most of the databases where Data Mining is
used are large. This paper reviews various algorithms and techniques that have been
brought forth since 1995 by researchers for implementing SVMs in a practical manner for …
Abstract
Support Vector Machine (SVM) has been successful in multiple areas and is widely accepted as the best off the shelf algorithm for classification. A standard SVM has O(n3) time and O(n3) space complexities, hence making it limited in its usability for large database. We know that in real world scenario, most of the databases where Data Mining is used are large. This paper reviews various algorithms and techniques that have been brought forth since 1995 by researchers for implementing SVMs in a practical manner for large databases.
Springer
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