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» Using Bayesian networks to analyze expression data
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KDD
1998
ACM
442views Data Mining» more  KDD 1998»
15 years 1 months ago
BAYDA: Software for Bayesian Classification and Feature Selection
BAYDA is a software package for flexible data analysis in predictive data mining tasks. The mathematical model underlying the program is based on a simple Bayesian network, the Na...
Petri Kontkanen, Petri Myllymäki, Tomi Siland...
BMCBI
2008
122views more  BMCBI 2008»
14 years 9 months ago
Determining gene expression on a single pair of microarrays
Background: In microarray experiments the numbers of replicates are often limited due to factors such as cost, availability of sample or poor hybridization. There are currently fe...
Robert W. Reid, Anthony A. Fodor
IFIP12
2008
14 years 11 months ago
Bayesian Networks Optimization Based on Induction Learning Techniques
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Paola Britos, Pablo Felgaer, Ramón Garc&iac...
WECWIS
2002
IEEE
130views ECommerce» more  WECWIS 2002»
15 years 2 months ago
Dynamic Netvalue Analyzer - A Pricing Plan Modeling Tool for ISPs Using Actual Network Usage Data
The current situation in the Internet service provider market shows that Internet service providers (ISPs) are still struggling to find sustainable business models. The challenge ...
Jörn Altmann, Lee Rhodes
TSP
2008
167views more  TSP 2008»
14 years 8 months ago
Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...
Kai Ni, John William Paisley, Lawrence Carin, Davi...