Macro_Consensus             package:clue             R Documentation

_G_o_r_d_o_n-_V_i_c_h_i _M_a_c_r_o_e_c_o_n_o_m_i_c _C_o_n_s_e_n_s_u_s _P_a_r_t_i_t_i_o_n _D_a_t_a

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

     The soft ("fuzzy") consensus partitions for the macroeconomic
     partition data given in Gordon and Vichi (2001).

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

     data("Macro_Consensus")

_F_o_r_m_a_t:

     A named cluster ensemble of four soft partitions of 21 countries
     terms into two classes.

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

     The elements of the ensemble are named '"MF1"', '"MF2"', '"JMF"',
     and '"S&S"', and correspond to the median partitions obtained by
     applying models 1, 2, and 3 in Gordon and Vichi (2001) and the
     approach in Sato and Sato (1994) to the macroeconomic partition
     data in Gordon and Vichi (2001), which are available as data set
     'Macro'.

_S_o_u_r_c_e:

     Table 4 in Gordon and Vichi (2001).

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

     A. D. Gordon and M. Vichi (2001). Fuzzy partition models for
     fitting a set of partitions. _Psychometrika_, *66*, 229-248.

     M. Sato and Y. Sato (1994). On a multicriteria fuzzy clustering
     method for 3-way data. _International Journal of Uncertainty,
     Fuzziness and Knowledge-Based Systems_, *2*, 127-142.

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

     ## Load the median consensus partitions.
     data("Macro_Consensus")
     ## Fuzziness using the Partition Coefficient.
     cl_fuzziness(Macro_Consensus)
     ## (Correponds to 1 - F in the source.)
     ## Dissimilarities:
     cl_dissimilarity(Macro_Consensus)
     cl_dissimilarity(Macro_Consensus, method = "comem")

