Ignore:
Timestamp:
Mar 5, 2008, 3:30:58 AM (14 years ago)
Author:
Peter
Message:

working on #75

File:
1 edited

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  • trunk/yat/classifier/NBC.h

    r1184 r1200  
    6464   
    6565    ///
    66     /// \brief Train the %classifier using training data and targets.
     66    /// \brief Train the NBC using training data and targets.
    6767    ///
    6868    /// For each class mean and variance are estimated for each
     
    7676
    7777    ///
    78     /// \brief Train the %classifier using weighted training data and
     78    /// \brief Train the NBC using weighted training data and
    7979    /// targets.
    8080    ///
     
    121121
    122122       \f$ P_j = \frac{1}{Z} \exp\left(-N\frac{\sum
    123        {w_i(x_i-\mu_i)^2}/(2\sigma_i^2)}{\sum w_i}\right)\f$,
    124        where \f$ \mu_i \f$ and \f$ \sigma_i^2 \f$ are the estimated
    125        mean and variance, respectively. Z is chosen such that
    126        total probability equals unity, \f$ \sum P_j = 1 \f$.
     123       {w_i(x_i-\mu_i)^2}/(2\sigma_i^2)}{\sum w_i}\right)
     124       \prod_i\frac{1}{\sqrt{2\pi\sigma_i^2}}\f$, where \f$ \mu_i \f$
     125       and \f$ \sigma_i^2 \f$ are the estimated mean and variance,
     126       respectively. Z is chosen such that total probability equals
     127       unity, \f$ \sum P_j = 1 \f$.
    127128
    128129       \note If parameters could not be estimated during training, due
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