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» Informative sampling for large unbalanced data sets
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COMAD
2008
15 years 2 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»
15 years 1 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»
15 years 1 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»
16 years 2 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
15 years 5 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