lvqinit                package:class                R Documentation

_I_n_i_t_i_a_l_i_z_e _a _L_V_Q _C_o_d_e_b_o_o_k

_D_e_s_c_r_i_p_t_i_o_n:

     Construct an initial codebook for LVQ methods.

_U_s_a_g_e:

     lvqinit(x, cl, size, prior, k=5)

_A_r_g_u_m_e_n_t_s:

       x: a matrix or data frame of training examples, `n' by `p'. 

      cl: the classifications for the training examples. A vector or
          factor of length `n'. 

    size: the size of the codebook. Defaults to `min(round(0.4*ng*(ng-1
          + p/2),0), n)' where `ng' is the number of classes. 

   prior: Probabilities to represent classes in the codebook. Default
          proportions in the training set. 

       k: k used for k-NN test of correct classification. Default is 5. 

_D_e_t_a_i_l_s:

     Selects `size' examples from the training set without replacement
     with proportions proportional to the prior or the original
     proportions.

_V_a_l_u_e:

     A codebook, represented as a list with components `x' and `cl'
     giving the examples and classes.

_R_e_f_e_r_e_n_c_e_s:

     Kohonen, T. (1990) The self-organizing map.   Proc. IEEE  78,
     1464-1480.

     Kohonen, T. (1995) Self-Organizing Maps. Springer, Berlin.

_S_e_e _A_l_s_o:

     `lvq1', `lvq2', `lvq3', `olvq1', `lvqtest'

_E_x_a_m_p_l_e_s:

     data(iris3)
     train <- rbind(iris3[1:25,,1],iris3[1:25,,2],iris3[1:25,,3])
     test <- rbind(iris3[26:50,,1],iris3[26:50,,2],iris3[26:50,,3])
     cl <- factor(c(rep("s",25),rep("c",25), rep("v",25)))
     cd <- lvqinit(train, cl, 10)
     lvqtest(cd, train)
     cd1 <- olvq1(train, cl, cd)
     lvqtest(cd1, train)

