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    » Predicting Time Series with Support Vector Machines
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    APBC
    2008
    233views Bioinformatics» more  APBC 2008»
    Predicting Nucleolar Proteins Using Support-Vector Machines
    14 years 11 months ago
    Predicting Nucleolar Proteins Using Support-Vector Machines
    Download  www.comp.nus.edu.sg
    Mikael Bodén
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    BMCBI
    2008
    105views more  BMCBI 2008»
    Predicting RNA-binding sites of proteins using support vector machines and evolutionary information
    14 years 10 months ago
    Predicting RNA-binding sites of proteins using support vector machines and evolutionary information
    Download  www.biomedcentral.com
    Cheng-Wei Cheng, Emily Chia-Yu Su, Jenn-Kang Hwang...
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    ESANN
    1998
    170views Neural Networks» more  ESANN 1998»
    Recurrent SOM with local linear models in time series prediction
    14 years 11 months ago
    Recurrent SOM with local linear models in time series prediction
    Download  www.dice.ucl.ac.be
    Recurrent Self-Organizing Map (RSOM) is studied in three di erent time series prediction cases. RSOM is used to cluster the series into local data sets, for which corresponding lo...
    Timo Koskela, Markus Varsta, Jukka Heikkonen, Kimm...
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    KES
    2007
    Springer
    95views Information Technology» more  KES 2007»
    Time Discretisation Applied to Anomaly Detection in a Marine Engine
    15 years 4 months ago
    Time Discretisation Applied to Anomaly Detection in a Marine Engine
    Download  userweb.port.ac.uk
    This paper introduces the problems associated with anomaly detection in a marine engine, and explains the benefits that the SAX representation brings to the field. Despite limita...
    Ian Morgan, Honghai Liu, George Turnbull, David J....
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    ML
    2000
    ACM
    103views Machine Learning» more  ML 2000»
    Nonparametric Time Series Prediction Through Adaptive Model Selection
    14 years 9 months ago
    Nonparametric Time Series Prediction Through Adaptive Model Selection
    Download  webee.technion.ac.il
    We consider the problem of one-step ahead prediction for time series generated by an underlying stationary stochastic process obeying the condition of absolute regularity, describi...
    Ron Meir
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