DocumentCode :
3251469
Title :
A comparative study of RNN for outlier detection in data mining
Author :
Williams, Graham ; Baxter, Rohan ; He, Hongxing ; Hawkins, Simon ; Gu, Lifang
Author_Institution :
Enterprise Data Min., CSIRO, Canberra, ACT, Australia
fYear :
2002
fDate :
2002
Firstpage :
709
Lastpage :
712
Abstract :
We have proposed replicator neural networks (RNNs) for outlier detection. We compare RNN for outlier detection with three other methods using both publicly available statistical datasets (generally small) and data mining datasets (generally much larger and generally real data). The smaller datasets provide insights into the relative strengths and weaknesses of RNNs. The larger datasets in particular test scalability and practicality of application.
Keywords :
data mining; neural nets; statistical databases; very large databases; data mining datasets; outlier detection; replicator neural networks; scalability; statistical datasets; Australia; Data mining; Databases; Feedforward systems; Helium; Intelligent networks; Multi-layer neural network; Neural networks; Recurrent neural networks; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on
Print_ISBN :
0-7695-1754-4
Type :
conf
DOI :
10.1109/ICDM.2002.1184035
Filename :
1184035
Link To Document :
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