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    JMLR
    2010
    95views more  JMLR 2010»
    Feature Extraction for Machine Learning: Logic-Probabilistic Approach
    13 years 2 months ago
    Feature Extraction for Machine Learning: Logic-Probabilistic Approach
    Download  featureselection.asu.edu
    The paper analyzes peculiarities of preprocessing of learning data represented in object data bases constituted by multiple relational tables with ontology on top of it. Exactly s...
    Vladimir Gorodetsky, Vladimir Samoilov
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    ECCV
    2008
    Springer
    206views Computer Vision» more  ECCV 2008»
    Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
    14 years 9 months ago
    Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
    Download  www.gkmm.tu-darmstadt.de
    Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
    Paul Schnitzspan, Mario Fritz, Bernt Schiele
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    COLING
    2002
    132views Computational Linguistics» more  COLING 2002»
    Efficient Support Vector Classifiers for Named Entity Recognition
    13 years 7 months ago
    Efficient Support Vector Classifiers for Named Entity Recognition
    Download  acl.ldc.upenn.edu
    Named Entity (NE) recognition is a task in which proper nouns and numerical information are extracted from documents and are classified into categories such as person, organizatio...
    Hideki Isozaki, Hideto Kazawa
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    GECCO
    2008
    Springer
    232views Optimization» more  GECCO 2008»
    An efficient SVM-GA feature selection model for large healthcare databases
    13 years 9 months ago
    An efficient SVM-GA feature selection model for large healthcare databases
    Download  www.cs.bham.ac.uk
    This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
    Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
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    LREC
    2010
    126views Education» more  LREC 2010»
    Predictive Features for Detecting Indefinite Polar Sentences
    13 years 9 months ago
    Predictive Features for Detecting Indefinite Polar Sentences
    Download  www.lrec-conf.org
    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
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