21 search results - page 1 / 5 » Learning to classify with missing and corrupted features |
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularl...
IJCNN
2007
IEEE
13 years 11 months ago
2007
IEEE
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...
SDM
2004
SIAM
13 years 6 months ago
2004
SIAM
We present a novel probabilistic multiple cause model for binary observations. In contrast to other approaches, the model is linear and it infers reasons behind both observed and ...
JMLR
2008
13 years 4 months ago
2008
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...