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A Supervised Machine Learning Approach with Re-training for Un- structured Document Classification in UBE

• Authors : Dr. Jatinderkumar; R. Saini; Dr. Apurva ...

Subjects: Unsolicited Bulk Email (UBE; Unstructured Document; Tokenization

• Source: http://www.dcc.ufla.br/infocomp/images/artigos/v9.3/art04.pdf.

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Unsupervised and Supervised Machine Learning in User Modeling for Intelligent Learning Environments

• Authors : Saleema Amershi; Cristina Conati; The Pennsylvania State University CiteSeerX Archives

Subjects: User modeling; unsupervised and supervised machine learning

• Source: http://www.cs.ubc.ca/~conati/my-papers/IUI07-10604SaleemaCAMERA.pdf.

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A Performance Survey of Public Domain Supervised Machine Learning Algorithms

• Authors : Peter W. Eklund; Anh Hoang; The Pennsylvania State University CiteSeerX Archives

Subjects: Categories and Subject Descriptors; I.1.2 [Symbolic and Algebraic Manipulation; Algorithms

• Source: http://www.int.gu.edu.au/kvo/reports/ml.ps.gz.

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An Empirical Comparison of Supervised Machine Learning Techniques in Bioinformatics

• Authors : Aik Choon Tan; David Gilbert; The Pennsylvania State University CiteSeerX Archives

Subjects: Supervised machine learning; bioinformatics; ensemble

• Source: http://www.brc.dcs.gla.ac.uk/~actan/papers/preprintAPBC2003.pdf.

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A Performance Survey of Public Domain Supervised Machine Learning Algorithms

• Authors : Peter W. Eklund; The Pennsylvania State University CiteSeerX Archives

Subjects: Categories and Subject Descriptors; I.1.2 [Symbolic and Algebraic Manipulation; Algorithms

• Source: http://www.kvocentral.com/kvopapers/7paper.pdf.

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Supervised Machine Learning: A Review of Classification Techniques. Informatica 31:249–268

• Authors : S. B. Kotsiantis; The Pennsylvania State University CiteSeerX Archives

Subjects: classifiers; data mining techniques; intelligent data analysis

• Source: http://www.informatica.si/PDF/31-3/11_Kotsiantis - Supervised Machine Learning - A Review of.pdf.

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Evaluating Supervised Machine Learning for Adapting Enterprise

• Authors : Joe Hoffert; Douglas Schmidt; The Pennsylvania State University CiteSeerX Archives

• Source: http://www.dre.vanderbilt.edu/~schmidt/PDF/IPCT2010-ADAMANT.pdf.

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Combining Unsupervised and Supervised Machine Learning to Build User Models for Intelligent Learning Environments

• Authors : Saleema Amin Amershi; The Pennsylvania State University CiteSeerX Archives

• Source: http://www.cs.ubc.ca/grads/resources/thesis/May07/Amershi_Saleema.pdf.

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Detecting authorship deception: a supervised machine learning approach using . . .

• Authors : Lisa Pearl; Mark Steyvers; The Pennsylvania State University CiteSeerX Archives

• Source: http://psiexp.ss.uci.edu/research/papers/PearlSteyvers_AuthorshipDeceptionRev.v.2.pdf.

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Sequence analysis SVM-HUSTLE—an iterative semi-supervised machine learning approach for pairwise protein remote homology detection

• Authors : Anuj R. Shah; Christopher S. Oehmen; Bobbie-jo Webb-robertson ...

• Source: http://cbio.ensmp.fr/~jvert/svn/bibli/local/Shah2008SVM-HUSTLE.pdf.

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