thresholds-class           package:Rmagpie           R Documentation

_t_h_r_e_s_h_o_l_d_s: _A _c_l_a_s_s _t_o _h_a_n_d_l_e _t_h_e _t_h_r_e_s_h_o_l_d_s _t_o _b_e _t_e_s_t_e_d _d_u_r_i_n_g _t_r_a_i_n_i_n_g _o_f _t_h_e _N_e_a_r_e_s_t
_S_h_r_u_n_k_e_n _C_e_n_t_r_o_i_d

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

     The Nearest Shrunken Centroid is computed using a threshold. This
     threshold is usually determined by finding the best threshold
     value over a set of values by finding the threshold leading to the
     best error rate assessed by cross-validation. This class stores
     the values of thresholds to be tried. If the user wants to use
     default values it's also possible.

_C_r_e_a_t_i_n_g _o_b_j_e_c_t_s:

     'new("thresholds")'

     Create an empty thresholds. The default thresholds values will be
     computed and this object updated as soon as it is linked in an
     assessment.

     'new("thresholds", optionValues)'

     Create a thresholds, containing the thresholds values defined by
     'optionValues'. The slot 'noOfOptions' is automatically updated.

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


     '_o_p_t_i_o_n_V_a_l_u_e_s': 'numeric' Values of the thresholds, if
          'optionValues' has length zero then the default thresholds
          values must be used. 

     '_n_o_O_f_O_p_t_i_o_n_s': 'numeric' Number of thresholds. 

_E_x_t_e_n_d_s:

     Class '"featureSelectionOptions"', directly.

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


     '_g_e_t_N_o_T_h_r_e_s_h_o_l_d_s(_t_h_r_e_s_h_o_l_d_s)' Retreive the number of the
          thresholds (slot noOfOptions)

     '_g_e_t_O_p_t_i_o_n_V_a_l_u_e_s(_t_h_r_e_s_h_o_l_d_s)',  '_g_e_t_O_p_t_i_o_n_V_a_l_u_e_s(_t_h_r_e_s_h_o_l_d_s)<-' 
          Retreive and modify the values of the thresholds (slot
          optionValues)

_A_u_t_h_o_r(_s):

     Camille Maumet

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

     'geneSubsets', 'assessment'

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

     # Empty thresholds, the default values will be used when added to an assessment
     emptThresholds <- new("thresholds")
     getOptionValues(emptThresholds)
     getNoThresholds(emptThresholds)

     # Another thresholds
     thresholds <- new("thresholds", optionValues=c(0,0.1,0.2,1,2))
     getOptionValues(thresholds)
     getNoThresholds(thresholds)

     # Set the thresholds
     newThresholds <- c(0.1,0.2,0.5,0.6,1)
     getOptionValues(thresholds) <- newThresholds
     getOptionValues(thresholds)
     getNoThresholds(thresholds)

