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FLAIRS
2000
13 years 5 months ago
Inferencing Bayesian Networks from Time Series Data Using Natural Selection
This paper describes a new framework for using natural selection to evolve Bayesian Networks for use in forecasting time series data. It extends current research by introducing a ...
Andrew J. Novobilski, Farhad Kamangar
IDA
2003
Springer
13 years 8 months ago
Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
Allan Tucker, Xiaohui Liu
AINA
2008
IEEE
13 years 10 months ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh
BMCBI
2007
169views more  BMCBI 2007»
13 years 3 months ago
Transcription factor target prediction using multiple short expression time series from Arabidopsis thaliana
Background: The central role of transcription factors (TFs) in higher eukaryotes has led to much interest in deciphering transcriptional regulatory interactions. Even in the best ...
Henning Redestig, Daniel Weicht, Joachim Selbig, M...
CVPR
1999
IEEE
14 years 5 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...