summarize               package:boost               R Documentation

_S_u_m_m_a_r_i_z_e _t_h_e _o_u_t_p_u_t _o_f _c_l_a_s_s_i_f_i_c_a_t_i_o_n _w_i_t_h _b_o_o_s_t_i_n_g _f_u_n_c_t_i_o_n_s

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

     Yields text and graphical output that summarizes the
     misclassifcation error rates that have been achieved with boosting
     methods

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

     summarize(boost.out, resp, mout = ncol(boost.out), grafik = TRUE)

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

boost.out: An R-object, as obtained from one of the functions
          'bagboost', 'logitboost', 'adaboost' or 'l2boost'.

    resp: A vector containing the class labels of the test instances.
          Needs to be coded by 0 and 1.

    mout: The number of boosting iterations for which the error rate
          shall be printed. Defaults to the number of iterations
          boosting has been run for.

  grafik: Logical, indicating whether a plot of the error rates is
          desired or not.

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

     Just verbatim and graphical output.

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

     Marcel Dettling

_R_e_f_e_r_e_n_c_e_s:

_o "Boosting for Tumor Classification with Gene Expression Data", Marcel
     Dettling and Peter B\"uhlmann. Bioinformatics (2003), Vol. 19, p.
     1061-1069.

_o "BagBoosting for Tumor Classification with Gene Expression Data",
     Marcel Dettling. To appear in Bioinformatics (2005).

_o Further information is available from the webpage <URL:
     http://stat.ethz.ch/~dettling>

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

     bagboost, logitboost, adaboost, l2boost

_E_x_a_m_p_l_e_s:

     data(leukemia, package = "boost")

     ## Dividing the leukemia dataset into training and test data
     xlearn <- leukemia.x[c(1:20, 34:38),]
     ylearn <- leukemia.y[c(1:20, 34:38)]
     xtest  <- leukemia.x[21:33,]
     ytest  <- leukemia.y[21:33]

     ## Classification with logitboost
     fit <- logitboost(xlearn, ylearn, xtest, presel=50, mfinal=20)
     summarize(fit, ytest)

