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» A Distance-Based Packing Method for High Dimensional Data
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ICPP
2000
IEEE
14 years 1 months ago
A Scalable Parallel Subspace Clustering Algorithm for Massive Data Sets
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
Harsha S. Nagesh, Sanjay Goil, Alok N. Choudhary
IEEEARES
2006
IEEE
14 years 2 months ago
Identifying Intrusions in Computer Networks with Principal Component Analysis
Most current anomaly Intrusion Detection Systems (IDSs) detect computer network behavior as normal or abnormal but cannot identify the type of attacks. Moreover, most current intr...
Wei Wang, Roberto Battiti
BMCBI
2010
126views more  BMCBI 2010»
13 years 9 months ago
A boosting method for maximizing the partial area under the ROC curve
Background: The receiver operating characteristic (ROC) curve is a fundamental tool to assess the discriminant performance for not only a single marker but also a score function c...
Osamu Komori, Shinto Eguchi
EMMCVPR
2001
Springer
14 years 1 months ago
Path Based Pairwise Data Clustering with Application to Texture Segmentation
Most cost function based clustering or partitioning methods measure the compactness of groups of data. In contrast to this picture of a point source in feature space, some data sou...
Bernd Fischer, Thomas Zöller, Joachim M. Buhm...
ISCAS
2008
IEEE
145views Hardware» more  ISCAS 2008»
14 years 3 months ago
Group learning using contrast NMF : Application to functional and structural MRI of schizophrenia
— Non-negative Matrix factorization (NMF) has increasingly been used as a tool in signal processing in the last couple of years. NMF, like independent component analysis (ICA) is...
Vamsi K. Potluru, Vince D. Calhoun