performance-class            package:ROCR            R Documentation

_C_l_a_s_s "_p_e_r_f_o_r_m_a_n_c_e"

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

     Object to capture the result of a performance evaluation,
     optionally collecting evaluations from several cross-validation or
     bootstrapping runs.

_D_e_t_a_i_l_s:

     A 'performance' object can capture information from four different
     evaluation scenarios:

        *  The behaviour of a cutoff-dependent performance measure
           across the range of all cutoffs (e.g. 'performance( predObj,
           'acc' )' ). Here, 'x.values' contains the cutoffs,
           'y.values' the corresponding values of the performance
           measure, and 'alpha.values' is empty.

        *  The trade-off between two performance measures across the
           range of all cutoffs (e.g. 'performance( predObj, 'tpr',
           'fpr' )' ). In this case, the cutoffs are stored in
           'alpha.values', while 'x.values' and 'y.values' contain the
           corresponding values of the two performance measures.

        *  A performance measure that comes along with an obligatory
           second axis (e.g. 'performance( predObj, 'ecost' )' ). Here,
           the measure values are stored in 'y.values', while the
           corresponding values of the obligatory axis are stored in
           'x.values', and 'alpha.values' is empty.

        *  A performance measure whose value is just a scalar (e.g.
           'performance( predObj, 'auc' )' ). The value is then stored
           in 'y.values', while 'x.values' and 'alpha.values' are
           empty.

_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 'performance' function.

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

     '_x._n_a_m_e': Performance measure used for the x axis.

     '_y._n_a_m_e': Performance measure used for the y axis.

     '_a_l_p_h_a._n_a_m_e': Name of the unit that is used to create the
          parametrized curve. Currently, curves can only be
          parametrized by cutoff, so 'alpha.name' is either 'none' or
          'cutoff'.

     '_x._v_a_l_u_e_s': A list in which each entry contains the x values of
          the curve of this particular cross-validation run.
          x.values[[i]], y.values[[i]], and alpha.values[[i]]
          correspond to each other.

     '_y._v_a_l_u_e_s': A list in which each entry contains the y values of
          the curve of this particular cross-validation run.

     '_a_l_p_h_a._v_a_l_u_e_s': A list in which each entry contains the cutoff
          values of the curve of this particular cross-validation run.

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

