63 search results - page 3 / 13 » Privacy-preserving imputation of missing data |
JSS
2007
13 years 7 months ago
2007
Effort prediction is a very important issue for software project management. Historical project data sets are frequently used to support such prediction. But missing data are oft...
PKDD
1999
Springer
13 years 11 months ago
1999
Springer
Abstract. In many applications of data mining a - sometimes considerable - part of the data values is missing. This may occur because the data values were simply never entered into...
ICTAI
2008
IEEE
14 years 1 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...
JSS
2008
13 years 7 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...
DKE
2008
13 years 7 months ago
2008
Handling missing data is a critical step to ensuring good results in data mining. Like most data mining algorithms, existing privacy-preserving data mining algorithms assume data ...