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» Outlier Detection for High Dimensional Data
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BMCBI
2006
146views more  BMCBI 2006»
14 years 9 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara
IQ
2007
14 years 11 months ago
Rule-Based Measurement Of Data Quality In Nominal Data
: Sufficiently high data quality is crucial for almost every application. Nonetheless, data quality issues are nearly omnipresent. The reasons for poor quality cannot simply be bla...
Jochen Hipp, Markus Müller, Johannes Hohendor...
ICDM
2002
IEEE
122views Data Mining» more  ICDM 2002»
15 years 2 months ago
Using Category-Based Adherence to Cluster Market-Basket Data
In this paper, we devise an efficient algorithm for clustering market-basket data. Different from those of the traditional data, the features of market-basket data are known to b...
Ching-Huang Yun, Kun-Ta Chuang, Ming-Syan Chen
103
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BMCBI
2010
190views more  BMCBI 2010»
14 years 9 months ago
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification alg
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...
IJCAI
2007
14 years 11 months ago
Detection of Cognitive States from fMRI Data Using Machine Learning Techniques
Over the past decade functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful technique to locate activity of human brain while engaged in a particular task or cogni...
Vishwajeet Singh, Krishna P. Miyapuram, Raju S. Ba...