NIPS
2004
13 years 6 months ago
2004
We propose a convex optimization based strategy to deal with uncertainty in the observations of a classification problem. We assume that instead of a sample (xi, yi) a distributio...
PODC
2010
ACM
13 years 6 months ago
2010
ACM
Low overhead analysis of large distributed data sets is necessary for current data centers and for future sensor networks. In such systems, each node holds some data value, e.g., ...
CIARP
2003
Springer
13 years 8 months ago
2003
Springer
Classification problems are traditionally focused on uniclass samples, that is, each sample of the training and test sets has one unique label, which is the target of the classific...
AICCSA
2007
IEEE
13 years 8 months ago
2007
IEEE
In this paper the Karnaugh and Quine-McCluskey methods are used for symbolic classification problem, and then these methods are compared with other famous available methods. Becau...
IWANN
1999
Springer
13 years 8 months ago
1999
Springer
Abstract: Support vector machines (SVMs) are primarily designed for 2-class classification problems. Although in several papers it is mentioned that the combination of K SVMs can b...
AINA
2010
IEEE
13 years 9 months ago
2010
IEEE
—Packet classification problem has received much attention and continued to be an important topic in recent years. In packet classification problem, each incoming packet should b...
ADBIS
2007
Springer
13 years 10 months ago
2007
Springer
In solving the classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets sto...