S. Stolfo, A. Prodromidis, S. Tselepsis, W. Lee, D. Fan and P. Chan JAM: Java Agents for Meta-learning over Distributed Databases. In Prod. Third Intl. Conf. Knowledge Discovery and Data Mining, 1997. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Using Conflicts Among Multiple Base Classifiers to Measure.. - Fan, Stolfo, Chan Self-citation (Stolfo Fan) (Correct)
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S. Stolfo, A. Prodromidis, S. Tselepsis, W. Lee, D. Fan and P. Chan JAM: Java Agents for Meta-learning over Distributed Databases. In Prod. Third Intl. Conf. Knowledge Discovery and Data Mining, 1997.
Recursive-Stacking To Improve The Accuracy of Combined.. - Fan, Stolfo, al. Self-citation (Stolfo Fan) (Correct)
....; C t (x) is the final outcome. The effectiveness of stacking to increase accuracy has been widely reported [4, 14, 15] Stacking is also a feasible approach to learn over inherently distributed data [4] The idea of stacking has been deployed and implemented as agents to attack credit card fraud [13]. Experiments in different domains have shown accuracy increases from 0.5 to 3 over any of the combined base classifiers. In this paper, we will discuss a problem called conflicts that hinders the accuracy improvement of stacking. We propose and discuss some methods to solve it. Conflicts were ....
S. Stolfo, A. Prodromidis, S. Tselepsis, W. Lee, D. Fan and P. Chan JAM: Java Agents for Metalearning over Distributed Databases. In Prod. Third Intl. Conf. Knowledge Discovery and Data Mining, 1997.
Agent-based Fraud and Intrusion Detection in.. - Stolfo, Fan.. (1997) (2 citations) Self-citation (Stolfo Prodromidis Fan) (Correct)
....4 shows that this approach works well. An important feature here is that each bank only exchanges its locally computed classifiers, and not their local data. Thus, we are able to demonstrate the principle that it is possible to share knowledge without disclosing data . 3 The JAM Architecture JAM [8] is architected as an agent based system, a distributed computing construct that is designed as an extension of OS environments. It is a distributed metalearning system that supports the launching of learning and meta learning agents to distributed database sites. JAM is implemented as a ....
S. Stolfo, A. Prodromidis, S. Tselepsis, W. Lee, D. Fan and P. Chan JAM: Java Agents for Meta-learning over Distributed Databases. In Prod. Third Intl. Conf. Knowledge Discovery and Data Mining, 1997.
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