genesel-class              package:CMA              R Documentation

"_g_e_n_e_s_e_l"

_D_e_s_c_r_i_p_t_i_o_n:

     Object returned from a call to 'GeneSelection'

_S_l_o_t_s:


     '_r_a_n_k_i_n_g_s': A list of matrices. For the two-class case and the
          multi-class case where a genuine multi-class method has been
          used for variable selection, the length of the list is one.
          Otherwise, it is named according to the different binary
          scenarios (e.g. '1 vs 3'). Each list element is a 'matrix'
          with rows corresponding  to iterations (different
          'learningsets') and columns to variables. Each row thus
          contains an index vector representing the order of the
          variables with respect to their variable importance (s. slot
          'importance')

     '_i_m_p_o_r_t_a_n_c_e': A list of matrices, with the same structure as
          described for the slot 'rankings'. Each row of these matrices
          are ordered according to 'rankings' and contain the variable
          importance measure (absolute value of test statistic or
          regression coefficient).

     '_m_e_t_h_o_d': Name of the method used for variable selection, s.
          'GeneSelection'.

     '_s_c_h_e_m_e': The scheme used in the case of a non-binary response,
          one of '"pairwise"', '"one-vs-all"' or '"multiclass"'.


_M_e_t_h_o_d_s:


     _s_h_o_w Use 'show(genesel-object)' for brief information

     _t_o_p_l_i_s_t Use 'toplist(genesel-object, k=10, iter = 1)' to display
          the top first 10 variables and their variable importance for
          the first iteration (first learningset), s.'toplist'.

     _p_l_o_t Use 'plot(genesel-object, k=10, iter=1)' to display a barplot
          of the variable importance of the top first 10 variables, s.
          'plot,genesel-method'

_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:

     'GeneSelection'

