16 search results - page 1 / 4 » Extreme learning machine for missing data using multiple imp... |
ICTAI
2008
IEEE
13 years 11 months ago
2008
IEEE
It is difficult to learn good classifiers when training data is missing attribute values. Conventional techniques for dealing with such omissions, such as mean imputation, general...
HIS
2004
13 years 6 months ago
2004
Microarray data often contains multiple missing genetic expression values that degrade the performance of statistical and machine learning algorithms. This paper presents a K rank...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
A logistic regression classification algorithm is developed for problems in which the feature vectors may be missing data (features). Single or multiple imputation for the missing...
JSS
2008
13 years 4 months ago
2008
Missing data is a widespread problem that can affect the ability to use data to construct effective prediction systems. We investigate a common machine learning technique that can...
KDD
2010
ACM
13 years 8 months ago
2010
ACM
Stroke is the third leading cause of death and the principal cause of serious long-term disability in the United States. Accurate prediction of stroke is highly valuable for early...