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PR
2006
108views more  PR 2006»
13 years 10 months 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
13 years 8 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
13 years 8 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...
PKDD
2007
Springer
146views Data Mining» more  PKDD 2007»
14 years 4 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»
14 years 2 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