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» The Predictability of Data Values
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BMCBI
2008
193views more  BMCBI 2008»
13 years 10 months ago
Missing value imputation for microarray gene expression data using histone acetylation information
Background: It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile ...
Qian Xiang, Xianhua Dai, Yangyang Deng, Caisheng H...
PARMA
2004
191views Database» more  PARMA 2004»
13 years 11 months ago
Identifying Most Predictive Items
Abstract. Frequent itemsets and association rules are generally accepted concepts in analyzing item-based databases. The Apriori-framework was developed for analyzing categorical d...
Markus Wawryniuk, Daniel A. Keim
ISCA
2000
IEEE
78views Hardware» more  ISCA 2000»
14 years 2 months ago
On the value locality of store instructions
Value locality, a recently discovered program attribute that describes the likelihood of the recurrence of previously-seen program values, has been studied enthusiastically in the...
Kevin M. Lepak, Mikko H. Lipasti
CGO
2008
IEEE
14 years 4 months ago
Prediction and trace compression of data access addresses through nested loop recognition
This paper describes an algorithm that takes a trace (i.e., a sequence of numbers or vectors of numbers) as input, and from that produces a sequence of loop nests that, when run, ...
Alain Ketterlin, Philippe Clauss
ECML
2007
Springer
14 years 4 months ago
Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
Tapani Raiko, Alexander Ilin, Juha Karhunen