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ICONIP
2008
13 years 11 months ago
An Evaluation of Machine Learning-Based Methods for Detection of Phishing Sites
In this paper, we present the performance of machine learning-based methods for detection of phishing sites. We employ 9 machine learning techniques including AdaBoost, Bagging, S...
Daisuke Miyamoto, Hiroaki Hazeyama, Youki Kadobaya...
ICML
2003
IEEE
14 years 10 months ago
Tackling the Poor Assumptions of Naive Bayes Text Classifiers
Naive Bayes is often used as a baseline in text classification because it is fast and easy to implement. Its severe assumptions make such efficiency possible but also adversely af...
Jason D. Rennie, Lawrence Shih, Jaime Teevan, Davi...
ICML
2003
IEEE
14 years 10 months ago
Incorporating Diversity in Active Learning with Support Vector Machines
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Klaus Brinker
DCC
2006
IEEE
14 years 9 months ago
Compression and Machine Learning: A New Perspective on Feature Space Vectors
The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
D. Sculley, Carla E. Brodley
ICMLA
2009
13 years 7 months ago
Alive on Back-feed Culprit Identification via Machine Learning
We describe an application of machine learning techniques toward the problem of predicting which network protector switch is the cause of an Alive on Back-Feed (ABF) event in the ...
Bert C. Huang, Ansaf Salleb-Aouissi, Philip Gross