Lambda pruning: an approximation of the string subsequence kernel for practical SVM classification and redundancy clustering

DOI10.1007/s11634-007-0012-1zbMath1183.68504OpenAlexW2037957123MaRDI QIDQ1042630

Florian Kleedorfer, Alexander K. Seewald

Publication date: 14 December 2009

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11634-007-0012-1

zbMATH Keywords

kernel methodsmachine learningstring kernelsmemory consumption estimationruntime estimation

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Efficient geometric-based computation of the string subsequence kernel

Cites Work

• 10.1162/153244302760200687
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Lambda pruning: an approximation of the string subsequence kernel for practical SVM classification and redundancy clustering