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ECML
2007
Springer
15 years 5 months ago
A Simple Lexicographic Ranker and Probability Estimator
Given a binary classification task, a ranker sorts a set of instances from highest to lowest expectation that the instance is positive. We propose a lexicographic ranker, LexRank,...
Peter A. Flach, Edson Takashi Matsubara
ML
2006
ACM
132views Machine Learning» more  ML 2006»
14 years 11 months ago
A suffix tree approach to anti-spam email filtering
We present an approach to email filtering based on the suffix tree data structure. A method for the scoring of emails using the suffix tree is developed and a number of scoring and...
Rajesh Pampapathi, Boris Mirkin, Mark Levene
SIGIR
2004
ACM
15 years 5 months ago
Focused named entity recognition using machine learning
In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that th...
Li Zhang, Yue Pan, Tong Zhang
IJAR
2010
105views more  IJAR 2010»
14 years 9 months ago
A tree augmented classifier based on Extreme Imprecise Dirichlet Model
In this paper we present TANC, i.e., a tree-augmented naive credal classifier based on imprecise probabilities; it models prior near-ignorance via the Extreme Imprecise Dirichlet ...
G. Corani, C. P. de Campos
JMLR
2010
154views more  JMLR 2010»
14 years 6 months ago
MOA: Massive Online Analysis
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collecti...
Albert Bifet, Geoff Holmes, Richard Kirkby, Bernha...