plotcp                 package: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'

