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IDA
1997
Springer
14 years 17 days ago
How to Find Big-Oh in Your Data Set (and How Not to)
The empirical curve bounding problem is de ned as follows. Suppose data vectors X Y are presented such that E(Y i]) = f(X i]) where f(x) is an unknown function. The problem is to a...
Catherine C. McGeoch, Doina Precup, Paul R. Cohen
JSS
2007
118views more  JSS 2007»
13 years 8 months ago
A new imputation method for small software project data sets
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...
Qinbao Song, Martin J. Shepperd
KDD
2007
ACM
165views Data Mining» more  KDD 2007»
14 years 8 months ago
Finding low-entropy sets and trees from binary data
The discovery of subsets with special properties from binary data has been one of the key themes in pattern discovery. Pattern classes such as frequent itemsets stress the co-occu...
Eino Hinkkanen, Hannes Heikinheimo, Heikki Mannila...
CIDR
2003
218views Algorithms» more  CIDR 2003»
13 years 9 months ago
Indexing Large Trajectory Data Sets With SETI
With the rapid increase in the use of inexpensive, location-aware sensors in a variety of new applications, large amounts of time-sequenced location data will soon be accumulated....
V. Prasad Chakka, Adam Everspaugh, Jignesh M. Pate...
VISUALIZATION
2005
IEEE
14 years 2 months ago
Query-Driven Visualization of Large Data Sets
We present a practical and general-purpose approach to large and complex visual data analysis where visualization processing, rendering and subsequent human interpretation is cons...
Kurt Stockinger, John Shalf, Kesheng Wu, E. Wes Be...