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» Learning Patterns in Noisy Data: The AQ Approach
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PR
2010
147views more  PR 2010»
15 years 2 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani
KDD
2004
ACM
237views Data Mining» more  KDD 2004»
16 years 5 months ago
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Mario Medvedovic, Junhai Guo
CVPR
2012
IEEE
13 years 7 months ago
The use of on-line co-training to reduce the training set size in pattern recognition methods: Application to left ventricle seg
The use of statistical pattern recognition models to segment the left ventricle of the heart in ultrasound images has gained substantial attention over the last few years. The mai...
Gustavo Carneiro, Jacinto C. Nascimento
IEICET
2007
127views more  IEICET 2007»
15 years 4 months ago
Integration of Learning Methods, Medical Literature and Expert Inspection in Medical Data Mining
abstraction and text mining methods to exploit the collected data. Furthermore, our visual discovery system D2MS allowed to actively and effectively working with physicians. Signi...
Tu Bao Ho, Saori Kawasaki, Katsuhiko Takabayashi, ...
BMCBI
2007
126views more  BMCBI 2007»
15 years 4 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...