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ICONIP
2008
13 years 9 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
2002
IEEE
14 years 8 months ago
Cranking: Combining Rankings Using Conditional Probability Models on Permutations
A new approach to ensemble learning is introduced that takes ranking rather than classification as fundamental, leading to models on the symmetric group and its cosets. The approa...
Guy Lebanon, John D. Lafferty
IJON
2010
148views more  IJON 2010»
13 years 5 months ago
Integration of heterogeneous data sources for gene function prediction using decision templates and ensembles of learning machin
Several solutions have been proposed to exploit the availability of heterogeneous sources of biomolecular data for gene function prediction, but few attention has been dedicated t...
Matteo Re, Giorgio Valentini
ML
2000
ACM
144views Machine Learning» more  ML 2000»
13 years 7 months ago
MultiBoosting: A Technique for Combining Boosting and Wagging
MultiBoosting is an extension to the highly successful AdaBoost technique for forming decision committees. MultiBoosting can be viewed as combining AdaBoost with wagging. It is abl...
Geoffrey I. Webb
ICML
1994
IEEE
13 years 11 months ago
Combining Top-down and Bottom-up Techniques in Inductive Logic Programming
This paper describes a new methodfor inducing logic programs from examples which attempts to integrate the best aspects of existingILP methodsintoa singlecoherent framework. In pa...
John M. Zelle, Raymond J. Mooney, Joshua B. Konvis...