179 search results - page 25 / 36 » Neural Learning from Unbalanced Data Using Noise Modeling |
KDD
2004
ACM
14 years 9 months ago
2004
ACM
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
DSMML
2004
Springer
14 years 2 months ago
2004
Springer
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
ESANN
2006
13 years 10 months ago
2006
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
GRC
2010
IEEE
13 years 10 months ago
2010
IEEE
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
NIPS
1998
13 years 10 months ago
1998
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...