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» Fast Support Vector Machine Classification using linear SVMs
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80
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NIPS
2000
14 years 11 months ago
Regularized Winnow Methods
In theory, the Winnow multiplicative update has certain advantages over the Perceptron additive update when there are many irrelevant attributes. Recently, there has been much eff...
Tong Zhang
BMCBI
2008
116views more  BMCBI 2008»
14 years 9 months ago
The combination approach of SVM and ECOC for powerful identification and classification of transcription factor
Background: Transcription factors (TFs) are core functional proteins which play important roles in gene expression control, and they are key factors for gene regulation network co...
Guangyong Zheng, Ziliang Qian, Qing Yang, Chaochun...
97
Voted
LREC
2010
126views Education» more  LREC 2010»
14 years 11 months ago
Predictive Features for Detecting Indefinite Polar Sentences
In recent years, text classification in sentiment analysis has mostly focused on two types of classification, the distinction between objective and subjective text, i.e. subjectiv...
Michael Wiegand, Dietrich Klakow
WACV
2002
IEEE
15 years 2 months ago
An Experimental Evaluation of Linear and Kernel-Based Methods for Face Recognition
In this paper we present the results of a comparative study of linear and kernel-based methods for face recognition. The methods used for dimensionality reduction are Principal Co...
Himaanshu Gupta, Amit K. Agrawal, Tarun Pruthi, Ch...
ICDM
2005
IEEE
161views Data Mining» more  ICDM 2005»
15 years 3 months ago
Making Logistic Regression a Core Data Mining Tool with TR-IRLS
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...
Paul Komarek, Andrew W. Moore