Kanishka Bhaduri

Member since: Sep 24, 2010, Mission Critical Technologies Inc

Distributed Decision-Tree Induction in Peer-to-Peer Systems

Shared by Kanishka Bhaduri, updated on Sep 22, 2010


Author(s) :
Kanishka Bhaduri, R. Wolff, C. Giannella, H. Kargupta

This paper offers a scalable and robust distributed algorithm for decision-tree induction in large peer-to-peer (P2P) environments. Computing a decision tree in such large distributed systems using standard centralized algorithms can be very communication-expensive and impractical because of the synchronization requirements. The problem becomes even more challenging in the distributed stream monitoring scenario where the decision tree needs to be updated in response to changes in the data distribution. This paper presents an alternate solution that works in a completely asynchronous manner in distributed environments and offers low communication overhead, a necessity for scalability. It also seamlessly handles changes in data and peer failures. The paper presents extensive experimental results to corroborate the theoretical claims.

show more info
Publication Name
Distributed Decision-Tree Induction in Peer-to-Peer Systems
Publication Location
Statistical Analysis and Data Mining 1(2): 85-103
Year Published


203.7 KB 397 downloads


Add New Comment

Kanishka's Projects (4)

Need help?

Visit our help center