Amanote Research
Register
Sign In
Probabilistic Interpretations and Bayesian Methods for Support Vector Machines
doi 10.1049/cp:19991090
Full Text
Open PDF
Abstract
Available in
full text
Date
January 1, 1999
Authors
P. Sollich
Publisher
IEE
Related search
On Bayesian Inference, Maximum Entropy and Support Vector Machines Methods
AIP Conference Proceedings
Astronomy
Physics
Speeding Up Support Vector Machines - Probabilistic Versus Nearest Neighbour Methods for Condensing Training Data
Support Vector Machines for Spam Categorization
IEEE Transactions on Neural Networks
Combining Pixel-Based and Object-Oriented Support Vector Machines Using Bayesian Probability Theory
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Instrumentation
Earth
Planetary Sciences
Environmental Science
Support Vector Machines for Polycategorical Classification
Lecture Notes in Computer Science
Computer Science
Theoretical Computer Science
Support Vector Machines for Unbalanced Multicategory Classification
Mathematical Problems in Engineering
Mathematics
Engineering
Wavelets and Support Vector Machines for Texture Classification
Fuzzy Support Vector Machines for Pattern Classification
Stock Market Trend Prediction Using Support Vector Machines and Variable Selection Methods
