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» Classifier Selection Based on Data Complexity Measures
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KDD
2001
ACM
150views Data Mining» more  KDD 2001»
15 years 10 months ago
Empirical bayes screening for multi-item associations
This paper considers the framework of the so-called "market basket problem", in which a database of transactions is mined for the occurrence of unusually frequent item s...
William DuMouchel, Daryl Pregibon
BMCBI
2007
145views more  BMCBI 2007»
14 years 9 months ago
Improved benchmarks for computational motif discovery
Background: An important step in annotation of sequenced genomes is the identification of transcription factor binding sites. More than a hundred different computational methods h...
Geir Kjetil Sandve, Osman Abul, Vegard Walseng, Fi...
BMCBI
2008
173views more  BMCBI 2008»
14 years 10 months ago
Improved machine learning method for analysis of gas phase chemistry of peptides
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...
WS
2010
ACM
14 years 8 months ago
Semantic web enabled software analysis
One of the most important decisions researchers face when analyzing software systems is the choice of a proper data analysis/exchange format. In this paper, we present EvoOnt, a s...
Jonas Tappolet, Christoph Kiefer, Abraham Bernstei...
CVPR
2006
IEEE
15 years 12 months ago
BoostMotion: Boosting a Discriminative Similarity Function for Motion Estimation
Motion estimation for applications where appearance undergoes complex changes is challenging due to lack of an appropriate similarity function. In this paper, we propose to learn ...
Shaohua Kevin Zhou, Bogdan Georgescu, Dorin Comani...