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» Informative sampling for large unbalanced data sets
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COMAD
2008
13 years 9 months ago
Disk-Based Sampling for Outlier Detection in High Dimensional Data
We propose an efficient sampling based outlier detection method for large high-dimensional data. Our method consists of two phases. In the first phase, we combine a "sampling...
Timothy de Vries, Sanjay Chawla, Pei Sun, Gia Vinh...
JCB
2002
70views more  JCB 2002»
13 years 7 months ago
Strong Feature Sets from Small Samples
For small samples, classi er design algorithms typically suffer from over tting. Given a set of features, a classi er must be designed and its error estimated. For small samples, ...
Seungchan Kim, Edward R. Dougherty, Junior Barrera...
BMCBI
2007
102views more  BMCBI 2007»
13 years 7 months ago
Setting up a large set of protein-ligand PDB complexes for the development and validation of knowledge-based docking algorithms
Background: The number of algorithms available to predict ligand-protein interactions is large and ever-increasing. The number of test cases used to validate these methods is usua...
Luis A. Diago, Persy Morell, Longendri Aguilera, E...
VIS
2008
IEEE
174views Visualization» more  VIS 2008»
14 years 9 months ago
Extensions of Parallel Coordinates for Interactive Exploration of Large Multi-Timepoint Data Sets
Parallel coordinate plots (PCPs) are commonly used in information visualization to provide insight into multi-variate data. These plots help to spot correlations between variables....
Jorik Blaas, Charl P. Botha, Frits H. Post
DAWAK
1999
Springer
13 years 12 months ago
Efficient Bulk Loading of Large High-Dimensional Indexes
Efficient index construction in multidimensional data spaces is important for many knowledge discovery algorithms, because construction times typically must be amortized by perform...
Christian Böhm, Hans-Peter Kriegel