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» Optimizing F-Measure with Support Vector Machines
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KDD
2008
ACM
167views Data Mining» more  KDD 2008»
14 years 8 months ago
A sequential dual method for large scale multi-class linear svms
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as w...
S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang...
IDEAL
2007
Springer
14 years 1 months ago
Influence of Wavelet Frequency and Orientation in an SVM-Based Parallel Gabor PCA Face Verification System
We present a face verification system using Parallel Gabor Principal Component Analysis (PGPCA) and fusion of Support Vector Machines (SVM) scores. The algorithm has been tested on...
Ángel Serrano, Isaac Martín de Diego...
IJCNN
2006
IEEE
14 years 1 months ago
Semi-Supervised Model Selection Based on Cross-Validation
We propose a new semi-supervised model selection method that is derived by applying the structural risk minimization principle to a recent semi-supervised generalization error bou...
Matti Kaariainen
SSDBM
2006
IEEE
121views Database» more  SSDBM 2006»
14 years 1 months ago
Time Series Analysis Using the Concept of Adaptable Threshold Similarity
The issue of data mining in time series databases is of utmost importance for many practical applications and has attracted a lot of research in the past years. In this paper, we ...
Johannes Aßfalg, Hans-Peter Kriegel, Peer Kr...
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
14 years 1 months ago
Is negative selection appropriate for anomaly detection?
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems are identified with the use of these shape-spaces, and the negative selection algori...
Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, C...