gausspr-class            package:kernlab            R Documentation

_C_l_a_s_s "_g_a_u_s_s_p_r"

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

     The Gaussian Processes object class

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects can be created by calls of the form 'new("gausspr", ...)'.
     or by calling the 'gausspr' function

_S_l_o_t_s:

     '_t_o_l': Object of class '"numeric"' contains tolerance of
          termination criteria

     '_k_e_r_n_e_l_f': Object of class '"kfunction"' contains the kernel
          function used

     '_k_p_a_r': Object of class '"list"' contains the kernel parameter
          used 

     '_k_c_a_l_l': Object of class '"list"' contains the used function call 

     '_t_y_p_e': Object of class '"character"' contains type of problem 

     '_t_e_r_m_s': Object of class '"ANY"' contains the terms representation
          of the symbolic model used (when using a formula)

     '_x_m_a_t_r_i_x': Object of class '"input"' containing the data matrix
          used 

     '_y_m_a_t_r_i_x': Object of class '"output"' containing the response
          matrix

     '_f_i_t_t_e_d': Object of class '"output"' containing the fitted values  

     '_l_e_v': Object of class '"vector"' containing the levels of the
          response (in case of classification) 

     '_n_c_l_a_s_s': Object of class '"numeric"' containing the number of
          classes (in case of classification) 

     '_a_l_p_h_a': Object of class '"listI"' containing the computes alpha
          values 

     '_a_l_p_h_a_i_n_d_e_x' Object of class '"list"' containing the indexes for
          the alphas in various classes (in multi-class problems).

     '_s_c_a_l_i_n_g' Object of class '"ANY"' containing the scaling
          coefficients of the data (when case 'scaled = TRUE' is used).

     '_n_v_a_r': Object of class '"numeric"' containing the computed
          variance

     '_e_r_r_o_r': Object of class '"numeric"' containing the training error

     '_c_r_o_s_s': Object of class '"numeric"' containing the cross
          validation error

     '_n._a_c_t_i_o_n': Object of class '"ANY"' containing the action
          performed in NA 

_M_e_t_h_o_d_s:

     _a_l_p_h_a 'signature(object = "gausspr")': returns the alpha vector

     _c_r_o_s_s 'signature(object = "gausspr")': returns the cross
          validation error 

     _e_r_r_o_r 'signature(object = "gausspr")': returns the training error 

     _f_i_t_t_e_d 'signature(object = "vm")': returns the fitted values 

     _k_c_a_l_l 'signature(object = "gausspr")': returns the call performed

     _k_e_r_n_e_l_f 'signature(object = "gausspr")': returns the kernel
          function used

     _k_p_a_r 'signature(object = "gausspr")': returns the kernel parameter
          used

     _l_e_v 'signature(object = "gausspr")': returns the response levels
          (in classification) 

     _t_y_p_e 'signature(object = "gausspr")': returns the type of problem

     _x_m_a_t_r_i_x 'signature(object = "gausspr")': returns the data matrix
          used

     _y_m_a_t_r_i_x 'signature(object = "gausspr")': returns the response
          matrix used

     _s_c_a_l_i_n_g 'signature(object = "gausspr")': returns the scaling
          coefficients of the data (when 'scaled = TRUE' is used)

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

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

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

     'gausspr',  'ksvm-class', 'vm-class'

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

     # train model
     data(iris)
     test <- gausspr(Species~.,data=iris,var=2)
     test
     alpha(test)
     error(test)
     lev(test)

