## Collective Mining of Bayesian Networks from Distributed Heterogeneous Data (2002)

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Citations: | 15 - 6 self |

### BibTeX

@MISC{Chen02collectivemining,

author = {R. Chen and K. Sivakumar and H. Kargupta},

title = {Collective Mining of Bayesian Networks from Distributed Heterogeneous Data},

year = {2002}

}

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### Abstract

We present a collective approach to learning a Bayesian network from distributed heterogenous data. In this approach, we first learn a local Bayesian network at each site using the local data. Then each site identifies the observations that are most likely to be evidence of coupling between local and non-local variables and transmits a subset of these observations to a central site. Another Bayesian network is learnt at the central site using the data transmitted from the local site. The local and central Bayesian networks are combined to obtain a collective Bayesian network, that models the entire data. Experimental results and theoretical justification that demonstrate the feasibility of our approach are presented.