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» Computing LTS Regression for Large Data Sets
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GECCO
2006
Springer
214views Optimization» more  GECCO 2006»
14 years 22 days ago
A new discrete particle swarm algorithm applied to attribute selection in a bioinformatics data set
Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...
EDBT
2004
ACM
172views Database» more  EDBT 2004»
14 years 9 months ago
Efficient Similarity Search for Hierarchical Data in Large Databases
Structured and semi-structured object representations are getting more and more important for modern database applications. Examples for such data are hierarchical structures inclu...
Karin Kailing, Hans-Peter Kriegel, Stefan Schö...
CCGRID
2010
IEEE
13 years 10 months ago
High Performance Dimension Reduction and Visualization for Large High-Dimensional Data Analysis
Abstract--Large high dimension datasets are of growing importance in many fields and it is important to be able to visualize them for understanding the results of data mining appro...
Jong Youl Choi, Seung-Hee Bae, Xiaohong Qiu, Geoff...
EGPGV
2004
Springer
147views Visualization» more  EGPGV 2004»
14 years 2 months ago
I/O Strategies for Parallel Rendering of Large Time-Varying Volume Data
This paper presents I/O solutions for the visualization of time-varying volume data in a parallel and distributed computing environment. Depending on the number of rendering proce...
Hongfeng Yu, Kwan-Liu Ma, Joel Welling
BMCBI
2008
171views more  BMCBI 2008»
13 years 9 months ago
A general approach to simultaneous model fitting and variable elimination in response models for biological data with many more
Background: With the advent of high throughput biotechnology data acquisition platforms such as micro arrays, SNP chips and mass spectrometers, data sets with many more variables ...
Harri T. Kiiveri