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Agent-Based Distributed Learning Applied to Fraud Detection (1999)  (Make Corrections)  (9 citations)
Andreas L. Prodromidis, Salvatore Stolfo



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Abstract: Inductive learning and classification techniques have been applied in many problems in diverse areas. In this paper we describe an AI-based approach that combines inductive learning algorithms and meta-learning methods as a means to compute accurate classification models for detecting electronic fraud. Inductive learning algorithms are used to compute detectors of anomalous or errant behavior over inherently distributed data sets and meta-learning methods integrate their collective... (Update)

Context of citations to this paper:   More

.... fraud detectors with extensive results (TP FP spread and cost model) from the mining of these credit card data sets can be found in [31]. 4.1 Computing Base Classifiers The first step involves the training of the base classifiers. We split each data set in 12 subsets...

...aggregate. For a binary classification problem, for example, where each classifier C i with weight 4 Andreas L. Prodromidis and Salvatore J. Stolfo w i casts a 0 vote for class y 1 and a 1 vote for class y 2 , the aggregate is given by: S(x) # K i=1 w i C i (x) # K i=1 w i...

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Designing Intrusion Detection Systems: Architectures.. - Mukkamala, Sung, Abraham   (Correct)
Distributed Data Mining Systems - Prodromidis (1999)   (Correct)
Intrusion Detection: A Bibliography - Mé, Michel (2001)   (Correct)

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BibTeX entry:   (Update)

A. L. Prodromidis and S. J. Stolfo. Agent-based distributed learning applied to fraud detection. In Sixteenth National Conference on Artificial Intelligence. Submitted for publication. http://citeseer.ist.psu.edu/prodromidis99agentbased.html   More

@misc{ prodromidis-agentbased,
  author = "A. Prodromidis and S. Stolfo",
  title = "Agent-based distributed learning applied to fraud detection",
  text = "A. L. Prodromidis and S. J. Stolfo. Agent-based distributed learning applied
    to fraud detection. In Sixteenth National Conference on Artificial Intelligence.
    Submitted for publication.",
  url = "citeseer.ist.psu.edu/prodromidis99agentbased.html" }
Citations (may not include all citations):
1262   Classification and Regression Trees (context) - Breiman, Friedman et al. - 1984



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