Space-Efficient Feature Maps for String Alignment Kernels

Space-Efficient Feature Maps for String Alignment Kernels

Abstract String kernels are attractive data analysis tools for analyzing string data. Among them, alignment kernels are known for their high prediction accuracies in string classifications when tested in combination with SVM in various applications. However, alignment kernels have a crucial drawback...

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Bibliographic Details
Main Authors: Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh
Format: Article
Language:English
Published: SpringerOpen 2020-05-01
Series:Data Science and Engineering
Subjects:
Feature maps
Kernel approximation
String alignment kernels
Online Access:https://doi.org/10.1007/s41019-020-00120-6

Internet

https://doi.org/10.1007/s41019-020-00120-6

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