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144
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ICDM
2009
IEEE
142views Data Mining» more  ICDM 2009»
15 years 2 months ago
Building Classifiers with Independency Constraints
In this paper we study the problem of classifier learning where the input data contains unjustified dependencies between some data attributes and the class label. Such cases arise...
Toon Calders, Faisal Kamiran, Mykola Pechenizkiy
NIPS
2008
15 years 6 months ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang
PAKDD
2005
ACM
128views Data Mining» more  PAKDD 2005»
15 years 10 months ago
A Framework for Incorporating Class Priors into Discriminative Classification
Abstract. Discriminative and generative methods provide two distinct approaches to machine learning classification. One advantage of generative approaches is that they naturally mo...
Rong Jin, Yi Liu
VLDB
1990
ACM
116views Database» more  VLDB 1990»
15 years 9 months ago
A Probabilistic Framework for Vague Queries and Imprecise Information in Databases
A probabilistic learning model for vague queries and missing or imprecise information in databases is described. Instead of retrieving only a set of answers, our approach yields a...
Norbert Fuhr
147
Voted
CEC
2009
IEEE
15 years 11 months ago
Evolving hypernetwork models of binary time series for forecasting price movements on stock markets
— The paper proposes a hypernetwork-based method for stock market prediction through a binary time series problem. Hypernetworks are a random hypergraph structure of higher-order...
Elena Bautu, Sun Kim, Andrei Bautu, Henri Luchian,...