compareTreecalcs            package:DAAG            R Documentation

_E_r_r_o_r _r_a_t_e _c_o_m_p_a_r_i_s_o_n_s _f_o_r _t_r_e_e-_b_a_s_e_d _c_l_a_s_s_i_f_i_c_a_t_i_o_n

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

     Compare error rates, between different functions and different
     selection rules, for an approximately equal random division of the
     data into a training and test set.

_U_s_a_g_e:

     compareTreecalcs(x = yesno ~ ., data = spam7, cp = 0.00025,
                      fun = c("rpart", "randomForest"))

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

       x: model formula

    data: an data frame in which to interpret the variables named in
          the formula

      cp: setting for the cost complexity parameter 'cp', used by
          rpart()

     fun: one or both of "rpart" and "randomForest"

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

     Data are randomly divided into two subsets, I and II. The
     function(s) are used in the standard way for calculations on
     subset I, and error rates returined that come from the
     calculations carried out by the function(s).  Predictions are made
     for subset II, allowing the calculation of a completely
     independent set of error rates.

_V_a_l_u_e:

     If 'rpart' is specified in 'fun', the following:

 rpSEcvI: the estimated cross-validation error rate when 'rpart()' is
          run on the training data (I), and the one-standard error rule
          is used

   rpcvI: the estimated cross-validation error rate when  'rpart()' is
          run on subset I, and the model used that gives the minimum
          cross-validated error rate

rpSEtest: the error rate when the model that leads to 'rpSEcvI' is used
          to make predictions for subset II

  rptest: the error rate when the model that leads to 'rpcvI' is used
          to make predictions for subset II

 nSErule: number of splits required by the one standard error rule

  nREmin: number of splits to give the minimum error

   rfcvI: the out-of-bag (OOB) error rate when  'randomForest()' is run
          on subset I

  rftest: the error rate when the model that leads to 'rfcvI' is used
          to make predictions for subset II

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

     John Maindonald

