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» Better Evaluation Metrics Lead to Better Machine Translation
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COLING
2008
13 years 10 months ago
Choosing the Right Translation: A Syntactically Informed Classification Approach
One style of Multi-Engine Machine Translation architecture involves choosing the best of a set of outputs from different systems. Choosing the best translation from an arbitrary s...
Simon Zwarts, Mark Dras
ICPR
2004
IEEE
14 years 9 months ago
Image Retrieval by Local Evaluation of Nonlinear Kernel Functions around Salient Points
Feature histograms based on the evaluation of Haar integrals with nonlinear kernel functions were used successfully for the purpose of invariant content based image retrieval. In ...
Alaa Halawani, Hans Burkhardt
PVLDB
2010
121views more  PVLDB 2010»
13 years 3 months ago
Efficient RkNN Retrieval with Arbitrary Non-Metric Similarity Measures
A RkNN query returns all objects whose nearest k neighbors contain the query object. In this paper, we consider RkNN query processing in the case where the distances between attri...
Deepak P, Prasad Deshpande
ICML
2002
IEEE
14 years 9 months ago
Learning Decision Trees Using the Area Under the ROC Curve
ROC analysis is increasingly being recognised as an important tool for evaluation and comparison of classifiers when the operating characteristics (i.e. class distribution and cos...
César Ferri, José Hernández-O...
ECSQARU
2001
Springer
14 years 29 days ago
An Empirical Investigation of the K2 Metric
Abstract. The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions...
Christian Borgelt, Rudolf Kruse