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GFKL
2007
Springer
158views Data Mining» more  GFKL 2007»
15 years 7 months ago
Investigating Classifier Learning Behavior with Experiment Databases
Experimental assessment of the performance of classification algorithms is an important aspect of their development and application on real-world problems. To facilitate this analy...
Joaquin Vanschoren, Hendrik Blockeel
EDM
2009
147views Data Mining» more  EDM 2009»
15 years 1 months ago
an Argument Learning Environment Using Agent-Based ITS (ALES)
This paper presents an agent-based educational environment to teach argument analysis (ALES). The idea is based on the Argumentation Interchange Format Ontology (AIF) using "W...
Safia Abbas, Hajime Sawamura
ICML
2008
IEEE
16 years 4 months ago
Discriminative parameter learning for Bayesian networks
Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwi...
KDD
2009
ACM
207views Data Mining» more  KDD 2009»
16 years 3 months ago
DynaMMo: mining and summarization of coevolving sequences with missing values
Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn ...
Lei Li, James McCann, Nancy S. Pollard, Christos F...
161
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ESANN
2007
15 years 4 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann