Sciweavers

711 search results - page 15 / 143
» Applying Support Vector Machines to Imbalanced Datasets
Sort
View
ICPR
2008
IEEE
15 years 6 months ago
Fast model selection for MaxMinOver-based training of support vector machines
OneClassMaxMinOver (OMMO) is a simple incremental algorithm for one-class support vector classification. We propose several enhancements and heuristics for improving model select...
Fabian Timm, Sascha Klement, Thomas Martinetz
IJCNN
2008
IEEE
15 years 6 months ago
Ranking and selecting clustering algorithms using a meta-learning approach
Abstract— We present a novel framework that applies a metalearning approach to clustering algorithms. Given a dataset, our meta-learning approach provides a ranking for the candi...
Marcílio Carlos Pereira de Souto, Ricardo B...
NECO
2008
108views more  NECO 2008»
14 years 11 months ago
An SMO Algorithm for the Potential Support Vector Machine
We describe a fast Sequential Minimal Optimization (SMO) procedure for solving the dual optimization problem of the recently proposed Potential Support Vector Machine (P-SVM). The...
Tilman Knebel, Sepp Hochreiter, Klaus Obermayer
ISMIR
2005
Springer
166views Music» more  ISMIR 2005»
15 years 5 months ago
Song-Level Features and Support Vector Machines for Music Classification
Searching and organizing growing digital music collections requires automatic classification of music. This paper describes a new system, tested on the task of artist identifica...
Michael I. Mandel, Dan Ellis
ICML
2004
IEEE
16 years 16 days ago
Multi-task feature and kernel selection for SVMs
We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is ...
Tony Jebara