RAB               package:MLInterfaces               R Documentation

_r_e_a_l _a_d_a_b_o_o_s_t (_F_r_i_e_d_m_a_n _e_t _a_l) (_a_n_d _d_i_s_c_r_e_t_e _a_d_a_b_o_o_s_t (_D_A_B))

_D_e_s_c_r_i_p_t_i_o_n:

_U_s_a_g_e:

     RAB(formula, data, maxiter=200, maxdepth=1)

_A_r_g_u_m_e_n_t_s:

 formula: formula - the response variable must be coded -1, 1

    data: data

 maxiter: maxiter

maxdepth: maxdepth - passed to rpart

_V_a_l_u_e:

     an instance of raboostCont

_A_u_t_h_o_r(_s):

     Vince Carey <stvjc@channing.harvard.edu>

_R_e_f_e_r_e_n_c_e_s:

     Friedman et al Ann Stat 28/2 337

_E_x_a_m_p_l_e_s:

     library(MASS)
     data(Pima.tr)
     data(Pima.te)
     Pima.all = rbind(Pima.tr, Pima.te)
     tonp = ifelse(Pima.all$type == "Yes", 1, -1)
     tonp = factor(tonp)
     Pima.all = data.frame(Pima.all[,1:7], mtype=tonp)
     fit1 = RAB(mtype~ped+glu+npreg+bmi+age, data=Pima.all[1:200,], maxiter=10, maxdepth=5)
     pfit1 = Predict(fit1, newdata=Pima.tr)
     table(Pima.tr$type, pfit1)

