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ECML
2007
Springer
14 years 4 months ago
Learning to Classify Documents with Only a Small Positive Training Set
Many real-world classification applications fall into the class of positive and unlabeled (PU) learning problems. In many such applications, not only could the negative training ex...
Xiaoli Li, Bing Liu, See-Kiong Ng
APAL
2004
81views more  APAL 2004»
13 years 10 months ago
The complexity of first-order and monadic second-order logic revisited
The model-checking problem for a logic L on a class C of structures asks whether a given L-sentence holds in a given structure in C. In this paper, we give super-exponential lower...
Markus Frick, Martin Grohe
SETN
2004
Springer
14 years 3 months ago
A Meta-classifier Approach for Medical Diagnosis
Abstract. Single classifiers, such as Neural Networks, Support Vector Machines, Decision Trees and other, can be used to perform classification of data for relatively simple proble...
George L. Tsirogiannis, Dimitrios S. Frossyniotis,...
NIPS
2004
13 years 11 months ago
Incremental Algorithms for Hierarchical Classification
We study the problem of hierarchical classification when labels corresponding to partial and/or multiple paths in the underlying taxonomy are allowed. We introduce a new hierarchi...
Nicolò Cesa-Bianchi, Claudio Gentile, Andre...
CORR
2000
Springer
84views Education» more  CORR 2000»
13 years 10 months ago
Robust Classification for Imprecise Environments
In real-world environments it usually is difficult to specify target operating conditions precisely, for example, target misclassification costs. This uncertainty makes building ro...
Foster J. Provost, Tom Fawcett