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ML
2000
ACM
154views Machine Learning» more  ML 2000»
9 years 6 months ago
Lazy Learning of Bayesian Rules
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
Zijian Zheng, Geoffrey I. Webb
CORR
2000
Springer
126views Education» more  CORR 2000»
9 years 6 months ago
Learning to Filter Spam E-Mail: A Comparison of a Naive Bayesian and a Memory-Based Approach
We investigate the performance of two machine learning algorithms in the context of antispam filtering. The increasing volume of unsolicited bulk e-mail (spam) has generated a nee...
Ion Androutsopoulos, Georgios Paliouras, Vangelis ...
CORR
2000
Springer
71views Education» more  CORR 2000»
9 years 6 months ago
An evaluation of Naive Bayesian anti-spam filtering
It has recently been argued that a Naive Bayesian classifier can be used to filter unsolicited bulk e-mail ("spam"). We conduct a thorough evaluation of this proposal on...
Ion Androutsopoulos, John Koutsias, Konstantinos C...
BMCBI
2010
104views more  BMCBI 2010»
9 years 7 months ago
Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies
Background: All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloi...
Maria Pamela C. David, Gisela P. Concepcion, Eduar...
DIM
2008
ACM
9 years 8 months ago
Anti-phishing based on automated individual white-list
In phishing and pharming, users could be easily tricked into submitting their username/passwords into fraudulent web sites whose appearances look similar as the genuine ones. The ...
Ye Cao, Weili Han, Yueran Le
FLAIRS
2000
9 years 8 months ago
Inferencing Bayesian Networks from Time Series Data Using Natural Selection
This paper describes a new framework for using natural selection to evolve Bayesian Networks for use in forecasting time series data. It extends current research by introducing a ...
Andrew J. Novobilski, Farhad Kamangar
IJCAI
2007
9 years 8 months ago
Learning to Identify Unexpected Instances in the Test Set
Traditional classification involves building a classifier using labeled training examples from a set of predefined classes and then applying the classifier to classify test instan...
Xiaoli Li, Bing Liu, See-Kiong Ng
FLAIRS
2008
9 years 9 months ago
Evolutionary Learning of Dynamic Naive Bayesian Classifiers
Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...
PAKDD
2000
ACM
128views Data Mining» more  PAKDD 2000»
9 years 10 months ago
A Comparative Study of Classification Based Personal E-mail Filtering
This paper addresses personal E-mail filtering by casting it in the framework of text classification. Modeled as semi-structured documents, Email messages consist of a set of field...
Yanlei Diao, Hongjun Lu, Dekai Wu
COMPSAC
2004
IEEE
9 years 10 months ago
Excalibur: A Personalized Meta Search Engine
General purpose Web search engines are becoming ineffective due to the rapid growth and changes in the contents of the World Wide Web. Meta-search engines help a bit by having a b...
Leo Yuen, Matthew Chang, Ying Kit Lai, Chung Keung...
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