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    IJCNN
    2000
    IEEE
    124views Neural Networks» more  IJCNN 2000»
    Support Vector Machine for Regression and Applications to Financial Forecasting
    14 years 24 days ago
    Support Vector Machine for Regression and Applications to Financial Forecasting
    Download  www.svms.org
    The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Net...
    Theodore B. Trafalis, Huseyin Ince
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    ACL
    2009
    166views Computational Linguistics» more  ACL 2009»
    A Novel Discourse Parser Based on Support Vector Machine Classification
    13 years 6 months ago
    A Novel Discourse Parser Based on Support Vector Machine Classification
    Download  www.aclweb.org
    This paper introduces a new algorithm to parse discourse within the framework of Rhetorical Structure Theory (RST). Our method is based on recent advances in the field of statisti...
    David duVerle, Helmut Prendinger
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    AAAI
    2008
    154views Intelligent Agents» more  AAAI 2008»
    In-the-Dark Network Traffic Classification Using Support Vector Machines
    13 years 10 months ago
    In-the-Dark Network Traffic Classification Using Support Vector Machines
    Download  www.cs.wfu.edu
    This work addresses the problem of in-the-dark traffic classification for TCP sessions, an important problem in network management. An innovative use of support vector machines (S...
    William H. Turkett Jr., Andrew V. Karode, Errin W....
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    ANNPR
    2006
    Springer
    140views Neural Networks» more  ANNPR 2006»
    Incremental Training of Support Vector Machines Using Truncated Hypercones
    14 years 5 days ago
    Incremental Training of Support Vector Machines Using Truncated Hypercones
    Download  www.lib.kobe-u.ac.jp
    We discuss incremental training of support vector machines in which we approximate the regions, where support vector candidates exist, by truncated hypercones. We generate the trun...
    Shinya Katagiri, Shigeo Abe
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    JSS
    2008
    317views more  JSS 2008»
    Predicting defect-prone software modules using support vector machines
    13 years 8 months ago
    Predicting defect-prone software modules using support vector machines
    Download  isi.kfupm.edu.sa
    Effective prediction of defectprone software modules can enable software developers to focus quality assurance activities and allocate effort and resources more efficiently. Supp...
    Karim O. Elish, Mahmoud O. Elish
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