65 search results - page 8 / 13 » Distributed Data Mining vs. Sampling Techniques: A Compariso... |
ALGORITHMICA
2006
13 years 7 months ago
2006
Abstract. In this paper we present a coarse-grained parallel algorithm, CONQUEST, for constructing boundederror summaries of high-dimensional binary attributed data in a distribute...
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
TCBB
2010
13 years 6 months ago
2010
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
CORR
2004
Springer
13 years 7 months ago
2004
Springer
We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies. Direct inference of in...
CIKM
2008
Springer
13 years 9 months ago
2008
Springer
Statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). However, real-world entities...