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» Classifier Selection Based on Data Complexity Measures
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GECCO
2003
Springer
127views Optimization» more  GECCO 2003»
15 years 3 months ago
Complex Function Sets Improve Symbolic Discriminant Analysis of Microarray Data
Abstract. Our ability to simultaneously measure the expression levels of thousands of genes in biological samples is providing important new opportunities for improving the diagnos...
David M. Reif, Bill C. White, Nancy Olsen, Thomas ...
ACL
2008
14 years 11 months ago
Word Clustering and Word Selection Based Feature Reduction for MaxEnt Based Hindi NER
Statistical machine learning methods are employed to train a Named Entity Recognizer from annotated data. Methods like Maximum Entropy and Conditional Random Fields make use of fe...
Sujan Kumar Saha, Pabitra Mitra, Sudeshna Sarkar
HIS
2004
14 years 11 months ago
Classification Ensembles for Shaft Test Data: Empirical Evaluation
: A-scans from ultrasonic testing of long shafts are complex signals. The discrimination of different types of echoes is of importance for non-destructive testing and equipment mai...
Kyungmi Lee, Vladimir Estivill-Castro
BMCBI
2010
158views more  BMCBI 2010»
14 years 10 months ago
A Bayesian network approach to feature selection in mass spectrometry data
Background: Time-of-flight mass spectrometry (TOF-MS) has the potential to provide non-invasive, high-throughput screening for cancers and other serious diseases via detection of ...
Karl W. Kuschner, Dariya I. Malyarenko, William E....
PRIS
2007
14 years 11 months ago
A Novel Distance Measure for Interval Data
Interval data is attracting attention from the data analysis community due to its ability to describe complex concepts. Since clustering is an important data analysis tool, extendi...
Jie Ouyang, Ishwar K. Sethi