confuMat-methods        package:MLInterfaces        R Documentation

_M_e_t_h_o_d_s _f_o_r _F_u_n_c_t_i_o_n _c_o_n_f_u_M_a_t _i_n _P_a_c_k_a_g_e '_M_L_I_n_t_e_r_f_a_c_e_s'

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

     compute the confusion matrix for a classifier's output

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

     _o_b_j = "_c_l_a_s_s_i_f_O_u_t_p_u_t" Typically, an instance of class
          'classifOutput' is built on a ``training'' subset of the
          input data, and the ``test'' subset's true class labels are
          available.  This method cross-tabulates the true labels of
          the test set against the predictions of the fitted
          classifier.

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

     library(golubEsets)
     data(golubMerge)
     smallG <- golubMerge[1:50,]
     k1 <- knnB(smallG, "ALL.AML", 1:30)
     confuMat(k1)

