stamPrediction-class          package:stam          R Documentation

_R_e_s_u_l_t_s _o_f _P_r_e_d_i_c_t_i_o_n_s _b_y _S_t_A_M

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

     Object of this class are returned by 'stam.predict' and contain
     prediction  results as they are computed by structured analysis of
     microarray data.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects can be created by calls of the form 
     'new("stamPrediction", fit, expr.mat, cls, testset)', but using 
     'stam.predict' is recommended.

_S_l_o_t_s:


     '_c_h_i_p': Object of class '"character"', the name of the chip for 
          which the classifier net is generated.

     '_n_o_d_e_s': Object of class '"list"', elements are of class 
          'stamINode' or 'stamLeaf', one for each remaining node in the
          classifier  net.

     '_c_l_a_s_s._l_a_b_e_l_s': Object of class '"character"', one name for each 
          class

     '_b_e_s_t._d_e_l_t_a': Object of class '"numeric"', shrinkage level used
          for  computing

     '_c_l_s': Object of class '"character"', class names for  each sample

     '_p_r_o_b_s': Object of class '"array"', matrix of prediction 
          probabilities [samples x classes x nodes]

     '_p_r_e_d_i_c_t_s': Object of class '"character"', overall prediction for 
          each sample

     '_t_e_s_t_s_e_t': Object of class '"numeric"', indeces of samples which 
          belong to the test set. The other samples are assumed to be
          the traiing set.

     '_n_o_d_e._r_e_s_u_l_t_s': Object of class '"list"', performance, redundancy,
           sensitivity and specificity per node

_M_e_t_h_o_d_s:


     _i_m_a_g_e 'signature(x = "stamPrediction")': molecular symptoms image,
          see  'image.stamPrediction' for details

     _p_r_i_n_t 'signature(x = "stamPrediction")': print information on
          prediction

     _w_r_i_t_e_H_T_M_L 'signature(x = "stamPrediction")': generate HTML
          information  on prediction, but using 'stam.writeHTML' is
          recommended

_A_u_t_h_o_r(_s):

     Claudio Lottaz

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

     'stam.predict', 'image.stamPrediction',  'stam.writeHTML'

