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» A Case Study for Learning from Imbalanced Data Sets
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AUSDM
2008
Springer
212views Data Mining» more  AUSDM 2008»
15 years 8 months ago
Clustering and Classification of Maintenance Logs using Text Data Mining
Spreadsheets applications allow data to be stored with low development overheads, but also with low data quality. Reporting on data from such sources is difficult using traditiona...
Brett Edwards, Michael Zatorsky, Richi Nayak
CORR
2012
Springer
170views Education» more  CORR 2012»
14 years 1 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
BMCBI
2008
173views more  BMCBI 2008»
15 years 6 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...
KDD
1994
ACM
125views Data Mining» more  KDD 1994»
15 years 10 months ago
Knowledge Discovery in Large Image Databases: Dealing with Uncertainties in Ground Truth
This paper discusses the problem of knowledge discovery in image databases with particular focus on the issues which arise when absolute ground truth is not available. It is often...
Padhraic Smyth, Michael C. Burl, Usama M. Fayyad, ...
TMI
2010
182views more  TMI 2010»
15 years 4 months ago
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
Seyoung Kim, Padhraic Smyth, Hal S. Stern