prediction-class            package:ROCR            R Documentation

_C_l_a_s_s "_p_r_e_d_i_c_t_i_o_n"

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

     Object to encapsulate numerical predictions together with the
     corresponding true class labels, optionally collecting predictions
     and labels for several cross-validation or bootstrapping runs.

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

     Objects can be created by using the 'prediction' function.

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

     '_p_r_e_d_i_c_t_i_o_n_s': A list, in which each element is a vector of
          predictions (the list has length > 1 for x-validation data.)

     '_l_a_b_e_l_s': Analogously, a list in which each element is a vector of
          true class labels.

     '_c_u_t_o_f_f_s': A list in which each element is a vector of all
          necessary cutoffs. Each cutoff vector consists of the
          predicted scores (duplicates removed), in descending order.

     '_f_p': A list in which each element is a vector of the number (not
          the rate!) of false positives induced by the cutoffs given in
          the corresponding 'cutoffs' list entry.

     '_t_p': As fp, but for true positives.

     '_t_n': As fp, but for true negatives.

     '_f_n': As fp, but for false negatives.

     '_n._p_o_s': A list in which each element contains the number of
          positive samples in the given x-validation run.

     '_n._n_e_g': As n.pos, but for negative samples.

     '_n._p_o_s._p_r_e_d': A list in which each element is a vector of the
          number of samples predicted as positive at the cutoffs given
          in the corresponding 'cutoffs' entry.

     '_n._n_e_g._p_r_e_d': As n.pos.pred, but for negatively predicted samples.

_N_o_t_e:

     Every 'prediction' object contains information about the 2x2
     contingency table consisting of tp,tn,fp, and fn, along with the
     marginal sums n.pos,n.neg,n.pos.pred,n.neg.pred, because these
     form the basis for many derived performance measures.

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

     Tobias Sing tobias.sing@mpi-sb.mpg.de, Oliver Sander
     osander@mpi-sb.mpg.de

_R_e_f_e_r_e_n_c_e_s:

     A detailed list of references can be found on the ROCR homepage at
     <URL: http://rocr.bioinf.mpi-sb.mpg.de>.

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

     'prediction', 'performance', 'performance-class',
     'plot.performance'

