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BMCBI
2010
229views more  BMCBI 2010»
14 years 10 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
DGO
2008
126views Education» more  DGO 2008»
14 years 11 months ago
Active learning for e-rulemaking: public comment categorization
We address the e-rulemaking problem of reducing the manual labor required to analyze public comment sets. In current and previous work, for example, text categorization techniques...
Stephen Purpura, Claire Cardie, Jesse Simons
BMCBI
2008
219views more  BMCBI 2008»
14 years 10 months ago
Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles
Background: Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detect...
Guangtao Ge, G. William Wong
IJMMS
2008
80views more  IJMMS 2008»
14 years 9 months ago
Real-time classification of evoked emotions using facial feature tracking and physiological responses
We present automated, real-time models built with machine learning algorithms which use videotapes of subjects' faces in conjunction with physiological measurements to predic...
Jeremy N. Bailenson, Emmanuel D. Pontikakis, Iris ...
PRIB
2009
Springer
135views Bioinformatics» more  PRIB 2009»
15 years 4 months ago
Sequential Hierarchical Pattern Clustering
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
Bassam Farran, Amirthalingam Ramanan, Mahesan Nira...