srbct                 package:dprep                 R Documentation

_T_h_e _K_h_a_n _e_t _a_l.'_s _s_m_a_l_l _r_o_u_n_d _b_l_o_o_d _c_e_l_l_s _d_a_t_a_s_e_t

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

     The sbrct dataset which contains information of 63 samples and
     2308 genes. The samples are distributed in four classes as
     follows: 8 Burkitt Lymphoma (BL), 23 Ewing Sarcoma (EWS), 12
     neuroblastoma (NB), and 20 rhabdomyosarcoma (RMS).  The last
     column contains the labels of the fourth classes

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

     data(srbct)

_F_o_r_m_a_t:

     A data frame containing 63 observations of 2308. The last column
     of the dat frame  contains the class labels for each observations.

_S_o_u_r_c_e:

     The data set was  obtained, as binary R file from Marcel
     Dettling's web site:

        *  <URL: http://stat.ethz.ch/~dettling/bagboost.html>

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

     Javed Khan, Jun S. Wei, Markus Ringner, Lao H. Saal, Marc Ladanyi,
     Frank Westermann, Frank Berthold, Manfred Schwab, Cristina R.
     Antonescu, Carsten Peterson, and  Paul S. Meltzer (2001).
     Classification and diagnostic prediction of cancers using gene
     expression profiling and artificial neural networks. Nature
     Medicine, Volume 7, Number 6, June

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

     #---z-score Normalization
     data(srbct)
     rangenorm(srbct,"znorm")
     #---feature selection using the RELIEF-----
     #relief(srbct,63,0.12)

