ASparameter-classes          package:arules          R Documentation

_C_l_a_s_s_e_s "_A_S_p_a_r_a_m_e_t_e_r", "_A_P_p_a_r_a_m_e_t_e_r", "_E_C_p_a_r_a_m_e_t_e_r" -
_S_p_e_c_i_f_y_i_n_g _t_h_e '_p_a_r_a_m_e_t_e_r' _A_r_g_u_m_e_n_t _o_f _a_p_r_i_o_r_i() _a_n_d _e_c_l_a_t()

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

     The 'ASparameter' class holds the mining parameters (e.g., minimum
     support) for the used mining algorithms.  'APparameter' and
     'ECparameter' directly extend 'ASparameter' with additional slots
     for parameters only suitable for the Apriori ('APparameter') or
     the Eclat algorithms ('ECparameter').

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

     A suitable default parameter object will be automatically created
     by the 'apriori' or the 'eclat' function.  By specifying a named
     list (names equal to slots) as 'parameter' argument for the
     'apriori' or the  'eclat' function, default values can be replaced
     by the values in the list. Objects can be created by calls of the
     form 'new("APparameter", ...)' or 'new("ECparameter", ...)'.

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

     Common slots defined in 'ASparameter':

     '_s_u_p_p_o_r_t': a numeric value for the  minimal support of an item set
          (default: 0.1)

     '_m_i_n_l_e_n': an integer value for the minimal number of items per
          item set (default: 1)

     '_m_a_x_l_e_n': an integer value for the maximal number of items per
          item set (default: 5)

     '_t_a_r_g_e_t': a character string  indicating the type of association
          mined. One of

             *  '"frequent itemsets"' 

             *  '"maximally frequent itemsets"'

             *  '"closed frequent itemsets"'

             *  '"rules"' (only available for Apriori) 

             *  '"hyperedgesets"' (only available for Apriori;  see
                references for the definition of association
                hyperedgesets)


     '_e_x_t': a logical indicating whether to produce extended
          information on quality measures (e.g., lhs.support) (default:
          'FALSE')

     Additional slots for Apriori in 'APparameter':

     '_c_o_n_f_i_d_e_n_c_e': a numeric value for the minimal confidence of
          rules/association hyperedges (default: 0.8)

     '_s_m_a_x': a numeric value for the maximal support of
          itemsets/rules/hyperedgesets (default: 1)

     '_a_r_e_m': a character string indicating the used additional rule
          evaluation measure (default: '"none"') given  by one of

          '"_n_o_n_e"': no additional evaluation measure

          '"_d_i_f_f"': absolute confidence difference

          '"_q_u_o_t"': difference of confidence quotient to 1

          '"_a_i_m_p"': absolute difference of improvement to 1

          '"_i_n_f_o"': information difference to prior

          '"_c_h_i_2"': normalized chi^2 measure


     '_a_v_a_l': a logical indicating whether to return the additional rule
          evaluation measure selected with 'arem'.

     '_m_i_n_v_a_l': a numeric value for the minimal value of additional
          evaluation measure selected with 'arem' (default: 0.1)

     '_o_r_i_g_i_n_a_l_S_u_p_p_o_r_t': a logical indicating whether to use for minimum
          support the original definition of the support of a rule (lhs
          and rhs) instead of lhs support.  Make sure to use 'ext =
          TRUE' if 'originalSupport' is set to 'FALSE' (default:
          'TRUE')

     Additional slots for Eclat in 'ECparameter':

     '_t_i_d_L_i_s_t_s': a logical indicating whether to return also a list of
          supporting transactions (transaction IDs) (default: 'FALSE')

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

     _c_o_e_r_c_e 'signature(from = "NULL", to = "APparameter")'

     _c_o_e_r_c_e 'signature(from = "list", to = "APparameter")'

     _c_o_e_r_c_e 'signature(from = "NULL", to = "ECparameter")'

     _c_o_e_r_c_e 'signature(from = "list", to = "ECparameter")'

     _s_h_o_w 'signature(object = "ASparameter")'

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

     Christian Borgelt (2004) _Apriori - Finding Association
     Rules/Hyperedges with the Apriori Algorithm_. <URL:
     http://fuzzy.cs.uni-magdeburg.de/~borgelt/apriori.html>

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

     'apriori', 'eclat'

