obsinfo                 package:CMA                 R Documentation

_C_l_a_s_s_i_f_i_a_b_i_l_i_t_y _o_f _o_b_s_e_r_v_a_t_i_o_n_s

_D_e_s_c_r_i_p_t_i_o_n:

     Some observations are harder to classify than others. It is
     frequently of interest to know which observations are consistenly
     misclassified; these are candiates for outliers or wrong class
     labels.

_A_r_g_u_m_e_n_t_s:

  object: An object of class 'evaluation', generated with 'scheme =
          "observationwise"'

threshold: threshold value of (observation-wise) performance measure,
          s. 'evaluation' that has to be exceeded in order to speak of
          consistent misclassification. If 'measure = "average
          probability"', then values _below_ 'threshold' are regarded
          as consistent misclassification. Note that the default values
          1 is not sensible in that case

    show: Should the information be printed ? Default is 'TRUE'.

_D_e_t_a_i_l_s:

     As not all observation must have been classified at least once,
     observations not classified at all are also shown.

_V_a_l_u_e:

     A list with two components 

misclassification: A 'data.frame' containing the indices of consistenly
          misclassfied observations and the corresponding performance
          measure.

notclassified: The indices of those observations not classfied at all,
          s. details.

_A_u_t_h_o_r(_s):

     Martin Slawski martin.slawski@campus.lmu.de

     Anne-Laure Boulesteix <URL: http://www.slcmsr.net/boulesteix>

_S_e_e _A_l_s_o:

     'evaluation'

