sfs                  package:dprep                  R Documentation

_S_e_q_u_e_n_t_i_a_l _F_o_r_w_a_r_d _S_e_l_e_c_t_i_o_n

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

     Applies the Sequential Forward Selection algorithm for  Feature
     Selection.

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

     sfs(data, method = c("lda", "knn", "rpart"), kvec = 5,
      repet = 10)

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

    data: dataset to be used for feature selection

  method: classifier to be used, currently only the lda, knn and rpart
          classifiers are supported 

    kvec: number of neighbors to use for the knn classification

   repet: number of time to repeat the selection.

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

     The best subset of features is initialized as the empty set and at
      each step a the feature that gives the highest correct
     classification rate along with the features already included is
     added to set.  The "best subset" of features is constructed based
     on the frequency  with which each attribute is selected in the
     number of repetitions given. Due to the time complexity of the
     algorithm its use is not recommended for a large number of
     attributes(say more than 1000).

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

bestsubset: subset of features that have been determined to be
          relevant. 

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

     Edgar Acuna

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

     Acua, E , (2003) A comparison of filters and wrappers for feature
     selection in supervised classification. Proceedings of  the
     Interface 2003 Computing Science and Statistics. Vol 34.

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

     #---- Sequential forward selection using the knn classifier----
     data(my.iris)
     sfs(my.iris,method="knn",kvec=3,repet=10)

