clara.object             package:cluster             R Documentation

_C_l_u_s_t_e_r_i_n_g _L_a_r_g_e _A_p_p_l_i_c_a_t_i_o_n_s (_C_L_A_R_A) _O_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     The objects of class '"clara"' represent a partitioning of a large
     dataset into clusters and are typically returned from 'clara'.

_V_a_l_u_e:

     A legitimate 'clara' object is a list with the following
     components:

  sample: labels or case numbers of the observations in the best
          sample, that is, the sample used by the 'clara' algorithm for
          the final partition.

 medoids: the medoids or representative objects of the clusters. It is
          a matrix with in each row the coordinates of one medoid.
          Possibly 'NULL', namely when the object resulted from
          'clara(*, medoids.x=FALSE)'. Use the following 'i.med' in
          that case.

   i.med: the _indices_ of the 'medoids' above: 'medoids <- x[i.med,]'
          where 'x' is the original data matrix in 'clara(x,*)'.

clustering: the clustering vector, see 'partition.object'.

objective: the objective function for the final clustering of the
          entire dataset.

clusinfo: matrix, each row gives numerical information for one cluster.
          These are the cardinality of the cluster (number of
          observations), the maximal and average dissimilarity between
          the observations in the cluster and the cluster's medoid.  
          The last column is the maximal dissimilarity between the
          observations in the cluster and the cluster's medoid, divided
          by the minimal dissimilarity between the cluster's medoid and
          the medoid of any other cluster. If this ratio is small, the
          cluster is well-separated from the other clusters. 

    diss: dissimilarity (maybe NULL), see 'partition.object'.

 silinfo: list with silhouette width information for the best sample,
          see 'partition.object'.

    call: generating call, see 'partition.object'.

    data: matrix, possibibly standardized, or NULL, see
          'partition.object'.

_M_e_t_h_o_d_s, _I_n_h_e_r_i_t_a_n_c_e:

     The '"clara"' class has methods for the following generic
     functions: 'print', 'summary'.

     The class '"clara"' inherits from '"partition"'. Therefore, the
     generic functions 'plot' and 'clusplot' can be used on a 'clara'
     object.

_S_e_e _A_l_s_o:

     'clara', 'dissimilarity.object', 'partition.object',
     'plot.partition'.