796 search results - page 29 / 160 » Effective Use of the KDD Process and Data Mining for Compute... |
KDD
2004
ACM
14 years 9 months ago
2004
ACM
Most data mining algorithms require the setting of many input parameters. Two main dangers of working with parameter-laden algorithms are the following. First, incorrect settings ...
KDD
2006
ACM
14 years 9 months ago
2006
ACM
To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
IPPS
2007
IEEE
14 years 3 months ago
2007
IEEE
For a grid middleware to perform resource allocation, prediction models are needed, which can determine how long an application will take for completion on a particular platform o...
KDD
2007
ACM
14 years 9 months ago
2007
ACM
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
KDD
2008
ACM
14 years 9 months ago
2008
ACM
Studying the association between quantitative phenotype (such as height or weight) and single nucleotide polymorphisms (SNPs) is an important problem in biology. To understand und...