

plotcp(rpart)                                R Documentation

_P_l_o_t _a _C_o_m_p_l_e_x_i_t_y _P_a_r_a_m_e_t_e_r _T_a_b_l_e _f_o_r _a_n _R_p_a_r_t _F_i_t

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

     Gives a visual representation of the cross-validation
     results in an `rpart' object.

_U_s_a_g_e_:

     plotcp(x, minline=T, lty=3, col=1,
            upper=c("size", "splits", "none"), ...)

_A_r_g_u_m_e_n_t_s_:

       x: an object of class `rpart'

 minline: whether a horizontal line is drawn 1SE above the
          minimum of the curve.

     lty: line type for this line

     col: colour for this line

   upper: what is plotted on the top axis: the size of the
          tree (the number of leaves), the number of splits
          or nothing.

     ...: additional plotting parameters

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

     The set of possible cost-complexity prunings of a tree
     from a nested set. For the geometric means of the
     intervals of values of `cp' for which a pruning is
     optimal, a cross-validation has (usually) been done in
     the initial construction by `rpart'. The `cptable' in
     the fit contains the mean and standard deviation of the
     errors in the cross-validated prediction against each
     of the geometric means, and these are plotted by this
     function. A good choice of `cp' for pruning is often
     the leftmost value for which the mean lies below the
     horizontal line.

_V_a_l_u_e_:

     None.

_S_i_d_e _E_f_f_e_c_t_s_:

     A plot is produced on the current graphical device.

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

     `rpart', `printcp', `rpart.object'

