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IJCNN
2007
IEEE
11 years 11 months ago
Evaluation of Performance Measures for SVR Hyperparameter Selection
— To obtain accurate modeling results, it is of primal importance to find optimal values for the hyperparameters in the Support Vector Regression (SVR) model. In general, we sea...
Koen Smets, Brigitte Verdonk, Elsa Jordaan
BMCBI
2007
142views more  BMCBI 2007»
11 years 5 months ago
Predicting and improving the protein sequence alignment quality by support vector regression
Background: For successful protein structure prediction by comparative modeling, in addition to identifying a good template protein with known structure, obtaining an accurate seq...
Minho Lee, Chan-seok Jeong, Dongsup Kim
PR
2007
104views more  PR 2007»
11 years 4 months ago
Optimizing resources in model selection for support vector machine
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
Mathias M. Adankon, Mohamed Cheriet
NECO
1998
119views more  NECO 1998»
11 years 5 months ago
Density Estimation by Mixture Models with Smoothing Priors
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
Akio Utsugi
SDM
2012
SIAM
235views Data Mining» more  SDM 2012»
9 years 7 months ago
Sampling Strategies to Evaluate the Performance of Unknown Predictors
The focus of this paper is on how to select a small sample of examples for labeling that can help us to evaluate many different classification models unknown at the time of sampl...
Hamed Valizadegan, Saeed Amizadeh, Milos Hauskrech...
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