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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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111
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ICML
2003
IEEE
16 years 1 months ago
Boosting Lazy Decision Trees
This paper explores the problem of how to construct lazy decision tree ensembles. We present and empirically evaluate a relevancebased boosting-style algorithm that builds a lazy ...
Xiaoli Zhang Fern, Carla E. Brodley
107
Voted
EVOW
2008
Springer
15 years 2 months ago
DEEPER: A Full Parsing Based Approach to Protein Relation Extraction
Abstract. Lexical variance in biomedical texts poses a challenge to automatic protein relation mining. We therefore propose a new approach that relies only on more general language...
Timur Fayruzov, Martine De Cock, Chris Cornelis, V...
ML
2006
ACM
15 years 15 days ago
Using duration models to reduce fragmentation in audio segmentation
We investigate explicit segment duration models in addressing the problem of fragmentation in musical audio segmentation. The resulting probabilistic models are optimised using Mar...
Samer A. Abdallah, Mark B. Sandler, Christophe Rho...
152
Voted
ESANN
2004
15 years 1 months ago
Data Mining Techniques on the Evaluation of Wireless Churn
This work focuses on one of the most critical issues to plague the wireless telecommunications industry today: the loss of a valuable subscriber to a competitor, also defined as ch...
Jorge Ferreira, Marley B. R. Vellasco, Marco Aur&e...
EMNLP
2008
15 years 2 months ago
Cheap and Fast - But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks
Human linguistic annotation is crucial for many natural language processing tasks but can be expensive and time-consuming. We explore the use of Amazon's Mechanical Turk syst...
Rion Snow, Brendan O'Connor, Daniel Jurafsky, Andr...