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» Evaluating learning algorithms and classifiers
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105
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EACL
2006
ACL Anthology
15 years 1 months ago
Automatic Acronym Recognition
This paper deals with the problem of recognizing and extracting acronymdefinition pairs in Swedish medical texts. This project applies a rule-based method to solve the acronym rec...
Dana Dannélls
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
15 years 4 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
COLING
2010
14 years 7 months ago
EMMA: A novel Evaluation Metric for Morphological Analysis
We present a novel Evaluation Metric for Morphological Analysis (EMMA) that is both linguistically appealing and empirically sound. EMMA uses a graphbased assignment algorithm, op...
Sebastian Spiegler, Christian Monson
99
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DATAMINE
2008
143views more  DATAMINE 2008»
15 years 19 days ago
Automatically countering imbalance and its empirical relationship to cost
Learning from imbalanced datasets presents a convoluted problem both from the modeling and cost standpoints. In particular, when a class is of great interest but occurs relatively...
Nitesh V. Chawla, David A. Cieslak, Lawrence O. Ha...
112
Voted
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 1 months ago
Constrained optimization for validation-guided conditional random field learning
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...