4578 search results - page 22 / 916 » Learning from Multi-source Data |
SDM
2007
SIAM
13 years 10 months ago
2007
SIAM
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
ICML
2005
IEEE
14 years 9 months ago
2005
IEEE
We propose a general framework for learning from labeled and unlabeled data on a directed graph in which the structure of the graph including the directionality of the edges is co...
ILP
2001
Springer
14 years 28 days ago
2001
Springer
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
MLDM
2007
Springer
14 years 2 months ago
2007
Springer
Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...
KDD
2008
ACM
14 years 9 months ago
2008
ACM
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...