couple                package:kernlab                R Documentation

_P_r_o_b_a_b_i_l_i_t_i_e_s _C_o_u_p_l_i_n_g _f_u_n_c_t_i_o_n

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

     'couple' is used to link class-probability estimates produced by
     pairwise coupling  in multi-class classification problems.

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

     couple(probin, coupler = "minpair")

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

  probin: The pairwise coupled class-probability estimates

 coupler: The type of coupler to use. Currently 'minpar' and 'pkpd' and
          'vote' are supported (see reference for more details). If
          'vote' is selected the returned value is a primitive estimate
          passed on given votes.

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

     As binary classification problems are much easier to solve many
     techniques exist to decompose multi-class classification problems
     into many binary classification problems (voting, error codes,
     etc.). Pairwise coupling (one against one) constructs a rule for
     discriminating between every pair of classes and then selecting
     the class with the most winning two-class decisions.  By using
     Platt's probabilities output for SVM one can get a class
     probability for each of the k(k-1)/2 models created in the
     pairwise  classification. The couple method implements various
     techniques to combine these probabilities.

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

     A matrix with the resulting probability estimates.

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

     Alexandros Karatzoglou 
      alexandros.karatzoglou@ci.tuwien.ac.at

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

     Ting-Fan Wu, Chih-Jen Lin, ruby C. Weng
      _Probability Estimates for Multi-class Classification by Pairwise
     Coupling_
      Neural Information Processing Symposium 2003 
      <URL: http://books.nips.cc/papers/files/nips16/NIPS2003_0538.pdf>

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

     'predict.ksvm', 'ksvm'

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

     ## create artificial pairwise probabilities
     pairs <- matrix(c(0.82,0.12,0.76,0.1,0.9,0.05),2)

     couple(pairs)

     couple(pairs, coupler="pkpd")

     couple(pairs, coupler ="vote")

