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» Limits on Learning Machine Accuracy Imposed by Data Quality
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KDD
1999
ACM
152views Data Mining» more  KDD 1999»
13 years 11 months ago
Applying General Bayesian Techniques to Improve TAN Induction
Tree Augmented Naive Bayes (TAN) has shown to be competitive with state-of-the-art machine learning algorithms [3]. However, the TAN induction algorithm that appears in [3] can be...
Jesús Cerquides
ICML
2007
IEEE
14 years 8 months ago
Beamforming using the relevance vector machine
Beamformers are spatial filters that pass source signals in particular focused locations while suppressing interference from elsewhere. The widely-used minimum variance adaptive b...
David P. Wipf, Srikantan S. Nagarajan
WCE
2007
13 years 8 months ago
A Comparison of Classification Techniques for Technical Text Passages
— Our work explores the use of several text categorization techniques for classification of manufacturing quality defect and service shop data sets into fixed categories. Althoug...
Mark M. Kornfein, Helena Goldfarb
JUCS
2006
185views more  JUCS 2006»
13 years 7 months ago
The Berlin Brain-Computer Interface: Machine Learning Based Detection of User Specific Brain States
We outline the Berlin Brain-Computer Interface (BBCI), a system which enables us to translate brain signals from movements or movement intentions into control commands. The main co...
Benjamin Blankertz, Guido Dornhege, Steven Lemm, M...
ALT
2000
Springer
13 years 11 months ago
Computationally Efficient Transductive Machines
In this paper1 we propose a new algorithm for providing confidence and credibility values for predictions on a multi-class pattern recognition problem which uses Support Vector mac...
Craig Saunders, Alexander Gammerman, Volodya Vovk