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» Classes and clusters in data analysis
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SSPR
2004
Springer
15 years 12 months ago
Learning from General Label Constraints
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
Tijl De Bie, Johan A. K. Suykens, Bart De Moor
NC
2007
129views Neural Networks» more  NC 2007»
15 years 6 months ago
Sorting of neural spikes: When wavelet based methods outperform principal component analysis
Sorting of the extracellularly recorded spikes is a basic prerequisite for analysis of the cooperative neural behavior and neural code. Fundamentally the sorting performance is deļ...
Alexey N. Pavlov, Valeri A. Makarov, Ioulia Makaro...
BMCBI
2006
136views more  BMCBI 2006»
15 years 6 months ago
Metric for Measuring the Effectiveness of Clustering of DNA Microarray Expression
Background: The recent advancement of microarray technology with lower noise and better affordability makes it possible to determine expression of several thousand genes simultane...
Raja Loganantharaj, Satish Cheepala, John Clifford
SCHOLARPEDIA
2011
14 years 9 months ago
N-body simulations
Abstract. Scientists’ ability to generate and collect massive-scale datasets is increasing. As a result, constraints in data analysis capability rather than limitations in the av...
RSFDGRC
2011
Springer
255views Data Mining» more  RSFDGRC 2011»
14 years 9 months ago
Construction and Analysis of Web-Based Computer Science Information Networks
WINACS (Web-based Information Network Analysis for Computer Science) is a project that incorporates many recent, exciting developments in data sciences to construct a Web-based co...
Jiawei Han