evaloutput-class             package:CMA             R Documentation

"_e_v_a_l_o_u_t_p_u_t"

_D_e_s_c_r_i_p_t_i_o_n:

     Object returned by the method 'evaluation'.

_S_l_o_t_s:


     '_s_c_o_r_e': A numeric vector of performance scores whose length
          depends on '"scheme"', s.below. It equals the number of
          iterations (number of different datasets) if '"scheme =
          iterationwise"' and the number of all observations in the
          complete dataset otherwise. As not necessarily all
          observation must be predicted at least one time, 'score' can
          also contain 'NA's for those observations not classified at
          all.

     '_m_e_a_s_u_r_e': performance measure used, s. 'evaluation'.

     '_s_c_h_e_m_e': scheme used, s. 'evaluation'

     '_m_e_t_h_o_d': name of the classifier that has been evaluated.

_M_e_t_h_o_d_s:


     _s_h_o_w Use 'show(evaloutput-object)' for brief information.

     _s_u_m_m_a_r_y Use 'summary(evaloutput-object)' to apply the classic
          'summary()' function to the slot 'score', s.
          'summary,evaloutput-method'

     _b_o_x_p_l_o_t Use 'boxplot(evaloutput-object)' to display a boxplot of
          the slot 'score', s. 'boxplot,evaloutput-method'.

     _o_b_s_i_n_f_o Use 'obsinfo(evaloutput-object, threshold)' to display all
          observations consistenly correctly or incorrectly classified
          (depending on the value of the argument 'threshold'), s.
          'obsinfo'.

_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'

