hclass                package:mclust                R Documentation

_C_l_a_s_s_i_f_i_c_a_t_i_o_n_s _f_r_o_m _H_i_e_r_a_r_c_h_i_c_a_l _A_g_g_l_o_m_e_r_a_t_i_o_n

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

     Determines the classifications corresponding to different numbers
     of groups given merge pairs from hierarchical agglomeration.

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

     hclass(hcPairs, G)

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

 hcPairs: A numeric two-column matrix in which the _i_th row gives the
          minimum  index for observations in each of the two clusters
          merged at the _i_th stage of agglomerative hierarchical
          clustering. 

       G: An integer or vector of integers giving the number of
          clusters for which the corresponding classfications are
          wanted. 

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

     A matrix with 'length(G)' columns, each column  corresponding to a
     classification. Columns are indexed by the character
     representation of the integers in 'G'.

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

     C. Fraley and A. E. Raftery (2002b). MCLUST:Software for
     model-based clustering, density estimation and discriminant
     analysis.  Technical Report, Department of Statistics, University
     of Washington.  See <URL: http://www.stat.washington.edu/mclust>.

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

     'hc', 'hcE'

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

     data(iris)
     irisMatrix <- iris[,1:4]

     hcTree <- hc(modelName="VVV", data = irisMatrix)
     cl <- hclass(hcTree,c(2,3))

     par(pty = "s", mfrow = c(1,1))
     clPairs(irisMatrix,cl=cl[,"2"])
     clPairs(irisMatrix,cl=cl[,"3"])

