outlier             package:randomForest             R Documentation

_C_o_m_p_u_t_e _o_u_t_l_y_i_n_g _m_e_a_s_u_r_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     Compute outlying measures based on a proximity matrix.

_U_s_a_g_e:

     ## Default S3 method:
     outlier(x, cls=NULL, ...)
     ## S3 method for class 'randomForest':
     outlier(x, ...)

_A_r_g_u_m_e_n_t_s:

       x: a proximity matrix (a square matrix with 1 on the diagonal
          and values between 0 and 1 in the off-diagonal positions); or
          an object of class 'randomForest', whose 'type' is not
          'regression'.

     cls: the classes the rows in the proximity matrix belong to.  If
          not given, all data are assumed to come from the same class.

     ...: arguments for other methods.

_V_a_l_u_e:

     A numeric vector containing the outlying measures.  The outlying
     measure of a case is computed as n / sum(squared proximity),
     normalized by subtracting the median and divided by the MAD,
     within each class.

_S_e_e _A_l_s_o:

     'randomForest'

_E_x_a_m_p_l_e_s:

     set.seed(1)
     iris.rf <- randomForest(iris[,-5], iris[,5], proximity=TRUE)
     plot(outlier(iris.rf), type="h",
          col=c("red", "green", "blue")[as.numeric(iris$Species)])

