cu.summary               package:rpart               R Documentation

_A_u_t_o_m_o_b_i_l_e _D_a_t_a _f_r_o_m '_C_o_n_s_u_m_e_r _R_e_p_o_r_t_s' _1_9_9_0

_D_e_s_c_r_i_p_t_i_o_n:

     The 'cu.summary' data frame has 117 rows and 5 columns, giving
     data on makes of cars taken from the April, 1990 issue of
     _Consumer Reports_.

_U_s_a_g_e:

     cu.summary

_F_o_r_m_a_t:

     This data frame contains the following columns:

     '_P_r_i_c_e' a numeric vector giving the list price in US dollars of a
          standard model

     '_C_o_u_n_t_r_y' of origin, a factor with levels 'Brazil' 'England'
          'France' 'Germany' 'Japan' 'Japan/USA' 'Korea' 'Mexico'
          'Sweden' 'USA'

     '_R_e_l_i_a_b_i_l_i_t_y' an ordered factor with levels 'Much worse' < 'worse'
          < 'average' < 'better' < 'Much better'

     '_M_i_l_e_a_g_e' fuel consumption miles per US gallon, as tested.

     '_T_y_p_e' a factor with levels 'Compact' 'Large' 'Medium' 'Small'
          'Sporty' 'Van'


_S_o_u_r_c_e:

     _Consumer Reports_, April, 1990, pp. 235-288 quoted in

     John M. Chambers and Trevor J. Hastie eds. (1992) _Statistical
     Models in S_, Wadsworth and Brooks/Cole, Pacific Grove, CA 1992,
     pp. 46-47.

_S_e_e _A_l_s_o:

     'car.test.frame'

_E_x_a_m_p_l_e_s:

     fit <- rpart(Price ~ Mileage + Type + Country, cu.summary)
     plot(fit, compress=TRUE)
     text(fit, use.n=TRUE)