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127
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PR
2006
108views more  PR 2006»
15 years 28 days ago
Boosted discriminant projections for nearest neighbor classification
In this paper we introduce a new embedding technique to find the linear projection that best projects labeled data samples into a new space where the performance of a Nearest Neig...
David Masip, Jordi Vitrià
EMNLP
2010
14 years 11 months ago
A Semi-Supervised Approach to Improve Classification of Infrequent Discourse Relations Using Feature Vector Extension
Several recent discourse parsers have employed fully-supervised machine learning approaches. These methods require human annotators to beforehand create an extensive training corp...
Hugo Hernault, Danushka Bollegala, Mitsuru Ishizuk...
ICPR
2010
IEEE
14 years 11 months ago
Boosting Bayesian MAP Classification
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...
115
Voted
PKDD
2007
Springer
146views Data Mining» more  PKDD 2007»
15 years 7 months ago
A Method for Multi-relational Classification Using Single and Multi-feature Aggregation Functions
This paper presents a novel method for multi-relational classification via an aggregation-based Inductive Logic Programming (ILP) approach. We extend the classical ILP representati...
Richard Frank, Flavia Moser, Martin Ester
AUSDM
2007
Springer
94views Data Mining» more  AUSDM 2007»
15 years 5 months ago
Classification for accuracy and insight: A weighted sum approach
This research presents a classifier that aims to provide insight into a dataset in addition to achieving classification accuracies comparable to other algorithms. The classifier c...
Anthony Quinn, Andrew Stranieri, John Yearwood